# Terrier Intelligence — full directory > A consolidated map of AI resources at Boston University. Generated 2026-09-24T07:37:06.105Z. This file is the complete contents of https://terrierintelligence.com: every AI-related lab, student club, class, and professor at Boston University that the directory lists, plus recent AI-related BU news. It is an independent, student-maintained directory and is not published by Boston University. Every entry below is followed by its canonical page URL. When citing a fact from this file, cite that page. The same data is available as JSON at https://terrierintelligence.com/api/v1/all.json, and a short index lives at https://terrierintelligence.com/llms.txt. Counts: 39 labs, 25 clubs, 81 classes, 222 professors, 40 news items. --- ## Labs (39) AI research labs, centers, and initiatives. ### Humanities & AI Lab (HAIL) https://terrierintelligence.com/labs/humanities-ai-lab An interdisciplinary research group examining social, political, and ethical questions raised by AI from both humanities and technical perspectives, open to undergraduate and graduate students. - Department: Philosophy - Topics: Ethics, Policy, Social Science, Humanities - Location: Department of Philosophy - Website: https://www.bu.edu/philo/community/the-humanities-and-artificial-intelligence-lab/ - Status: active - Last verified: 2026-08-23 ### AI Research Initiative (AIR) https://terrierintelligence.com/labs/ai-research-initiative A cross-disciplinary research initiative developing computational models for machine intelligence: systems that reliably make decisions, reason about data, and communicate with humans. - Department: Hariri Institute - Topics: Computer Vision, ML Theory, NLP/LLMs, Generative AI/Tools - Website: https://www.bu.edu/hic/centers-and-initiatives-2/air/ - Status: active - Last verified: 2026-08-22 ### AI and Education Initiative https://terrierintelligence.com/labs/ai-and-education-initiative A cross-disciplinary initiative facilitating research on AI and human learning across ages and contexts, drawing on computing, education, and social-science perspectives. - Department: Hariri Institute · Wheelock - Topics: Education, NLP/LLMs, Computer Vision, Robotics - Status: active - Last verified: 2026-08-22 ### Evidence-Based AI in Learning (EVAL) Industry Collaborative https://terrierintelligence.com/labs/eval-collaborative A research collaborative evaluating how generative AI tools affect K-12 learning outcomes through independent studies conducted with EdTech industry partners. - Department: Hariri Institute - Topics: Education, Statistics - Website: https://www.bu.edu/hic/centers-initiatives-labs/eval/ - Status: active - Last verified: 2026-08-22 ### Artificial Intelligence and Emerging Media (AIEM) https://terrierintelligence.com/labs/aiem A media-focused research group applying machine learning, natural language processing, and computer vision to study how emerging media shape mass and interpersonal communication. - Department: COM · Hariri Institute - Topics: ML Theory, NLP/LLMs, Computer Vision - Website: https://sites.bu.edu/aiem/ - Status: active - Last verified: 2026-08-23 ### Batman Lab https://terrierintelligence.com/labs/batman-lab A machine-learning research group building explainable, data-efficient models for medical image analysis, with attention to multimodal fusion and causal inference. - Department: Electrical & Computer Engineering - Topics: Healthcare, ML Theory, Computer Vision - Website: https://www.batman-lab.com/ - Status: active - Last verified: 2026-08-22 ### BioMolecular Engineering Research Center (BMERC) https://terrierintelligence.com/labs/bmerc A computational biology research center developing computer-assisted methods to analyze and design the structure, function, and regulation of biological macromolecules. - Department: Bioinformatics · BME - Topics: Healthcare, Data Science - Website: https://www.bu.edu/bmerc/ - Status: active - Last verified: 2026-08-22 ### Bridges from AI to Understanding and Reprograming Biology (2AI2BIO) https://terrierintelligence.com/labs/2ai2bio A bioinformatics-focused research group bridging AI and biomedical science, developing machine-learning algorithms to decode, model, and reprogram genomic and biological systems. - Department: Bioinformatics · BME · CS - Topics: Healthcare, ML Theory, Data Science - Website: https://sites.bu.edu/phenogeno/ - Status: active - Last verified: 2026-08-22 ### Business Insights through Text (BIT) Lab https://terrierintelligence.com/labs/bit-lab A business-analytics research group extracting consumer-behavior and market insights from text data using causal inference, interpretable ML, and neural language processing. - Department: Questrom - Topics: Data Science, NLP/LLMs, Generative AI/Tools - Website: https://www.leedokyun.com/bitlab.html - Status: active - Last verified: 2026-08-22 ### Computer Vision and Learning Group https://terrierintelligence.com/labs/computer-vision-and-learning-group A computer-vision research group studying how models adapt across data distributions, with work on domain adaptation, learning with limited labels, and vision-language tasks. - Department: Computer Science - Topics: Computer Vision, ML Theory, NLP/LLMs - Website: https://ai.bu.edu/ - Status: active - Last verified: 2026-08-22 ### Data Science & Machine Learning Lab (Saligrama Lab) https://terrierintelligence.com/labs/data-science-machine-learning-lab A machine-learning research group developing methods that work under resource constraints and limited supervision, with related projects on bias mitigation and network analysis. - Department: Electrical & Computer Engineering - Topics: ML Theory, Computer Vision, Statistics - Website: https://sites.bu.edu/data/ - Status: active - Last verified: 2026-08-22 ### Image and Video Computing (IVC) https://terrierintelligence.com/labs/image-and-video-computing A computer-vision research group developing methods for image and video analysis, machine learning, and human-computer interaction across medical and scientific applications. - Department: Computer Science - Topics: Computer Vision, ML Theory, HCI - Website: https://www.bu.edu/cs/ivc/ - Status: active - Last verified: 2026-08-25 ### Shape Lab https://terrierintelligence.com/labs/shape-lab A computer-graphics research group focused on computational fabrication, designing algorithms that connect digital 3D models to physically buildable objects and structures. - Department: Computer Science - Topics: HCI - Website: https://shape.bu.edu/ - Status: active - Last verified: 2026-08-22 ### Visual Information Processing (VIP) Lab https://terrierintelligence.com/labs/vip-lab A computer-vision research group building camera-based sensing systems that count and locate people in large indoor spaces using overhead fisheye imagery. - Department: Electrical & Computer Engineering - Topics: Computer Vision, ML Theory, Statistics - Website: https://vip.bu.edu/ - Status: active - Last verified: 2026-08-22 ### AI Development Accelerator (AIDA) https://terrierintelligence.com/labs/ai-development-accelerator-aida A university-wide initiative guiding responsible generative-AI adoption across BU, providing supported AI tools, training, and events for students, faculty, and staff. - Department: University-wide - Topics: Generative AI/Tools, Education, Ethics, Boston University - Website: https://www.bu.edu/aida/ - Status: active - Last verified: 2026-08-22 ### Algorithmic Lens on Experimental Biology Laboratory https://terrierintelligence.com/labs/algorithmic-lens-on-experimental-biology-laboratory A computational-biology research group using the mathematics of machine learning to design biological experiments that reveal how cells and tissues are organized. - Department: Biomedical Engineering / Biology / CDS - Topics: Healthcare, ML Theory, Data Science - Website: https://www.algobiolab.com - Status: active - Last verified: 2026-08-22 ### Artificial and Biological Intelligence Lab https://terrierintelligence.com/labs/artificial-and-biological-intelligence-lab A computational-neuroscience research group building mathematical and ML models of how populations of neurons compute to produce behaviors such as decision-making and movement. - Department: Biomedical Engineering - Topics: ML Theory, Healthcare - Website: https://depasquale-lab.github.io/ - Status: active - Last verified: 2026-08-22 ### Barnes Group https://terrierintelligence.com/labs/barnes-group A climate-focused research group developing interpretable AI methods to study Earth system variability, predictability, and change across time and space. - Department: Earth & Environment / CDS - Topics: ML Theory, AI Safety, Environment - Website: https://barnes-research.com/ - Status: active - Last verified: 2026-09-11 ### BU Robotics Laboratory https://terrierintelligence.com/labs/bu-robotics-laboratory An experimental robotics facility housing a motion-capture system, autonomous ground and aerial vehicles, and an on-site workshop for building robots. - Department: College of Engineering / CARS - Topics: Robotics, ML Theory - Website: https://sites.bu.edu/robotics/ - Status: active - Last verified: 2026-08-22 ### Center for Autonomous and Robotics Systems (CARS) https://terrierintelligence.com/labs/center-for-autonomous-and-robotics-systems-cars An interdisciplinary engineering center studying the science of autonomy, robotic vehicles and manipulators, and micron-scale robots that manipulate living cells. - Department: College of Engineering - Topics: Robotics, ML Theory - Website: https://www.bu.edu/eng/2018/03/12/center-for-autonomous-and-robotics-systems/ - Status: active - Last verified: 2026-08-22 ### Computational Imaging Systems Lab https://terrierintelligence.com/labs/computational-imaging-systems-lab A computational-imaging research group combining physics-based optical models with deep learning to build microscopy and measurement systems for neuroscience, cancer research, and semiconductor metrology. - Department: Electrical & Computer Engineering - Topics: Computer Vision, Healthcare, ML Theory - Website: https://sites.bu.edu/tianlab/ - Status: active - Last verified: 2026-08-22 ### Dependable Computing Laboratory https://terrierintelligence.com/labs/dependable-computing-laboratory A formal-methods research group pairing computational proof techniques with machine learning to build safe, reliable, and secure hardware and software systems. - Department: Electrical & Computer Engineering - Topics: AI Safety, ML Theory, Robotics, Security - Website: https://sites.bu.edu/depend/ - Status: active - Last verified: 2026-08-22 ### Digital Business Institute Generative AI Lab https://terrierintelligence.com/labs/digital-business-institute-generative-ai-lab A business-school research initiative examining how generative AI affects firms, operations, markets, and work, including large language model reliability and algorithmic bias. - Department: Questrom / Digital Business Institute - Topics: Generative AI/Tools, NLP/LLMs, Data Science - Website: https://www.bu.edu/dbi/ - Status: active - Last verified: 2026-08-22 ### Human-AI Interaction in Recruiting & Employment (HIRE) Lab https://terrierintelligence.com/labs/human-ai-interaction-in-recruiting-employment-hire-lab An economics-focused research group studying how AI and digital platforms reshape hiring, labor-market matching, and work, using platform data and randomized experiments. - Department: Questrom / Information Systems - Topics: HCI, Policy, Data Science - Website: https://www.emmawiles.com/ - Status: active - Last verified: 2026-08-22 ### Hybrid and Networked Systems (HyNeSs) Lab https://terrierintelligence.com/labs/hybrid-and-networked-systems-hyness-lab A control-theory research group combining formal methods, dynamics, and machine learning to design provably correct behavior for robots and autonomous vehicles. - Department: Mechanical Engineering / ECE / Systems Engineering - Topics: Robotics, AI Safety, ML Theory - Website: https://sites.bu.edu/hyness/ - Status: inactive - Last verified: 2026-08-22 ### Kolachalama Lab https://terrierintelligence.com/labs/kolachalama-lab A medical-AI research group creating machine-learning methods shaped to clinical problems, from dementia assessment to trial design, rather than forcing problems onto existing tools. - Department: Medicine / Computer Science / CDS - Topics: Healthcare, Computer Vision, NLP/LLMs - Website: https://vkola-lab.github.io/ - Status: active - Last verified: 2026-08-22 ### Security Lab (SeclaBU) https://terrierintelligence.com/labs/seclabu A security-focused research group applying program analysis, machine learning, and computational social science to software vulnerabilities and harmful online activity. - Department: Electrical & Computer Engineering - Topics: AI Safety, ML Theory, NLP/LLMs, Security - Website: https://seclab.bu.edu/ - Status: active - Last verified: 2026-08-22 ### Machine Learning Research Group https://terrierintelligence.com/labs/machine-learning-research-group A department-wide research community whose faculty build intelligent systems that learn to make decisions, reason about data, and communicate with people. - Department: Computer Science - Topics: ML Theory, Computer Vision, NLP/LLMs, Robotics, HCI - Website: https://www.bu.edu/cs/research-groups/ml/ - Status: active - Last verified: 2026-08-22 ### Material Robotics Laboratory https://terrierintelligence.com/labs/material-robotics-laboratory A soft-robotics research group designing flexible, sensorized surgical instruments and the micro-scale manufacturing techniques needed to build them for minimally invasive procedures. - Department: Mechanical Engineering - Topics: Robotics, Healthcare, Computer Vision - Website: https://sites.bu.edu/mrl/ - Status: active - Last verified: 2026-08-22 ### Multi-Robot Systems Lab https://terrierintelligence.com/labs/multi-robot-systems-lab A robotics-focused research group designing collaborative robot teams that make fast, decentralized decisions and adapt to unknown agents and environments. - Department: Mechanical Engineering - Topics: Robotics, HCI - Website: https://sites.bu.edu/pierson/ - Status: active - Last verified: 2026-08-22 ### Network Optimization and Control Laboratory https://terrierintelligence.com/labs/network-optimization-and-control-laboratory A research group focused on optimization, machine learning, and control, developing data-driven methods for networks, autonomous systems, and health analytics. - Department: Systems Engineering / ECE - Topics: ML Theory, Robotics, Healthcare, NLP/LLMs - Website: https://sites.bu.edu/paschalidis/ - Status: active - Last verified: 2026-08-22 ### Neural Systems Analysis Laboratory (NSA Lab) https://terrierintelligence.com/labs/nsa-lab A neuroengineering-focused research group developing AI algorithms that analyze neuroimaging, electrophysiology, and genetics data to understand and treat brain disorders. - Department: Electrical & Computer Engineering - Topics: Healthcare, Computer Vision, ML Theory - Website: https://www.nsa-lab.org/ - Status: active - Last verified: 2026-08-22 ### Performance and Energy-Aware Computing Laboratory (PeacLab) https://terrierintelligence.com/labs/performance-and-energy-aware-computing-laboratory-peaclab A computing-systems research group applying machine learning to energy-efficient computing, from large-scale system analytics to sustainable AI data center management. - Department: Electrical & Computer Engineering - Topics: Environment, ML Theory, Data Science - Website: https://www.bu.edu/peaclab/ - Status: active - Last verified: 2026-08-22 ### Robotics & Autonomous Systems Teaching and Innovation Center (RASTIC) https://terrierintelligence.com/labs/robotics-autonomous-systems-teaching-and-innovation-center-rastic A robotics teaching and innovation facility where engineering students design, build, and test robotic systems with staff guidance and mentoring. - Department: College of Engineering - Topics: Robotics, Computer Vision, ML Theory - Website: https://www.bu.edu/eng/academics/departments-and-divisions/mechanical-engineering/rastic/ - Status: active - Last verified: 2026-08-22 ### Vision and Graphics Research Group https://terrierintelligence.com/labs/vision-and-graphics-research-group A computer-science research group spanning computer vision, graphics, and human-computer interaction, with machine learning methods applied across visual computing problems. - Department: Computer Science - Topics: Computer Vision, HCI, ML Theory - Website: https://www.bu.edu/cs/research-groups/vg/ - Status: active - Last verified: 2026-08-22 ### Human-to-Everything (H2X) Lab https://terrierintelligence.com/labs/human-to-everything-h2x-lab A robotics and AI research group building autonomous systems that assist people in real time, from driving perception to accessible navigation. - Department: Electrical & Computer Engineering - Topics: Robotics, Computer Vision, ML Theory - Website: https://eshed1.github.io/ - Status: active - Last verified: 2026-08-22 ### tinlab https://terrierintelligence.com/labs/tinlab A computational-linguistics research group studying meaning, generalization, evaluation, and the representations underlying language in humans and machine-learning models. - Department: Linguistics · Computer Science · CDS - Topics: NLP/LLMs, ML Theory, HCI - Website: https://najoung.kim/tinlab/ - Status: active - Last verified: 2026-09-22 ### Software & Application Innovation Lab (SAIL) https://terrierintelligence.com/labs/sail A research-software lab in the Hariri Institute that builds software, data systems, and secure generative-AI tools for Boston University research teams. - Department: Hariri Institute - Topics: Generative AI/Tools, NLP/LLMs, Healthcare - Location: 665 Commonwealth Ave., 12th Floor - Website: https://sail.codes - Status: active - Last verified: 2026-09-23 ### Rafik B. Hariri Institute for Computing and Computational Science & Engineering https://terrierintelligence.com/labs/hariri-institute-for-computing A university-wide research institute that brings together faculty and students from BU's 13 schools to advance computing, AI, and data science research. - Department: University-wide - Topics: Data Science, Healthcare, Education, Boston University - Location: Duan Family Center for Computing & Data Sciences, 665 Commonwealth Ave, 11th Floor - Website: https://www.bu.edu/hic/ - Status: active - Last verified: 2026-09-22 --- ## Clubs (25) AI-related student organizations. ### AI Safety & Alignment https://terrierintelligence.com/clubs/ai-safety-alignment A student organization focused on ensuring AI benefits everyone, running cohort-based fellowships in technical alignment and AI policy alongside a policy-analysis lab. - Topics: ML Theory, AI Safety, Policy - Meets: Weekly fellowships & events - Application status: Closed - Website: https://buaisa.org/ - Instagram: @bu.aisa - Contact: contact@buaisa.org - Last verified: 2026-09-19 ### AI Society https://terrierintelligence.com/clubs/ai-society A student organization focused on AI and ML that aims to make the field approachable through workshops, community events, and collaborative student projects. - Topics: NLP/LLMs, ML Theory, Generative AI/Tools - Application status: Open - Website: https://www.buaisociety.com/ - Instagram: @buaisociety - Contact: buais@bu.edu - Last verified: 2026-08-22 ### Machine Intelligence Community (BUMIC) https://terrierintelligence.com/clubs/bumic A student organization focused on machine intelligence education, meeting to discuss ML research papers and pursue member-led projects in a community setting. - Topics: ML Theory, NLP/LLMs - Application status: Closed - Last verified: 2026-08-22 ### BU Data Science Association https://terrierintelligence.com/clubs/bu-data-science-association A student organization focused on data science skill-building, running hands-on workshops and group projects that support portfolios and career preparation. - Topics: Data Science, Statistics - Application status: Open - Instagram: @bu_dsa - Last verified: 2026-08-22 ### Women in Data Science (WiDS) https://terrierintelligence.com/clubs/women-in-data-science A student organization focused on supporting women and underrepresented genders in data science through events such as workshops, speaker panels, and hackathons. - Topics: Data Science, Statistics - Application status: Open - Instagram: @bu_wids - Last verified: 2026-08-22 ### BostonHacks https://terrierintelligence.com/clubs/bostonhacks A student organization focused on organizing an annual 24-hour hackathon at BU, where student teams build software projects and attend beginner-friendly workshops. - Topics: Generative AI/Tools - Application status: Open - Last verified: 2026-08-22 ### Competitive Programming Club (BUCPC) https://terrierintelligence.com/clubs/competitive-programming-club A student organization focused on competitive programming, holding regular practice sessions on algorithmic problems and preparing members for intercollegiate programming contests. - Topics: ML Theory - Application status: Open - Last verified: 2026-08-22 ### BU Quantum https://terrierintelligence.com/clubs/bu-quantum A student organization focused on quantum computing, running beginner bootcamp lessons, programming workshops, and research talks spanning theory and software implementation. - Topics: ML Theory - Application status: Open - Last verified: 2026-08-22 ### CleanTech Club https://terrierintelligence.com/clubs/cleantech-club A student organization focused on environmentally sustainable technology, with meetings and projects centered on green engineering, clean innovation, and campus energy conservation. - Topics: Environment - Application status: Open - Last verified: 2026-08-22 ### Computer Science Club (CSC) https://terrierintelligence.com/clubs/computer-science-club A student organization focused on career preparation in computer science, offering resume workshops, mock technical interviews, and general guidance for CS and non-CS students. - Topics: Education - Application status: Open - Last verified: 2026-08-22 ### Cybersecurity Club https://terrierintelligence.com/clubs/cybersecurity-club A student organization focused on cybersecurity awareness, building a community for students interested in how security leadership protects organizations from cyber threats. - Topics: Security - Application status: Open - Last verified: 2026-08-22 ### Forge Design Studios https://terrierintelligence.com/clubs/forge-design-studios A student organization focused on pre-professional design practice, running workshops, an apprenticeship program, and a nationwide design competition for emerging designers. - Topics: HCI, Generative AI/Tools - Application status: Open - Last verified: 2026-08-22 ### Game Development Club https://terrierintelligence.com/clubs/game-development-club A student organization focused on video game design and development, offering a learning space where members collaborate on building game-making skills. - Topics: HCI - Application status: Open - Last verified: 2026-08-22 ### Girls Who Code https://terrierintelligence.com/clubs/girls-who-code A student organization focused on creating a judgment-free, approachable space for women entering coding, with programming built around skill-building and networking. - Topics: Education - Application status: Open - Last verified: 2026-08-22 ### Hack4Impact https://terrierintelligence.com/clubs/hack4impact A student organization focused on building software for nonprofits, with technical teams developing web and mobile applications for social good under student leads. - Topics: Generative AI/Tools, Data Science - Application status: Open - Last verified: 2026-08-22 ### HackHardware https://terrierintelligence.com/clubs/hackhardware A student organization focused on projects that combine hardware and software engineering, running hackathons, workshops, guest lectures, and technical demonstrations. - Topics: Robotics - Application status: Open - Last verified: 2026-08-22 ### High Performance Computing (BUHPC) https://terrierintelligence.com/clubs/high-performance-computing A student organization focused on high-performance computing, running workshops on software optimization and fielding teams for intercollegiate student cluster competitions. - Topics: Data Science - Application status: Open - Last verified: 2026-08-22 ### Mars Rover Club (BUMRC) https://terrierintelligence.com/clubs/mars-rover-club A student organization focused on building a Mars rover for the annual University Rover Challenge, including an autonomous navigation and traversal mission. - Topics: Robotics, Computer Vision - Application status: Open - Last verified: 2026-08-22 ### Women in Computer Science (WiCS) https://terrierintelligence.com/clubs/women-in-computer-science A student organization focused on supporting women in computer science through a peer community, mentorship, and events connecting students with the field. - Topics: Education - Application status: Open - Last verified: 2026-08-22 ### BU AR/VR https://terrierintelligence.com/clubs/bu-ar-vr A student organization focused on augmented and virtual reality, the interactive technologies that overlay digital content on physical surroundings or build immersive simulated environments. - Topics: HCI, Computer Vision, Generative AI/Tools - Application status: Apply Later - Contact: msachdev@bu.edu - Last verified: 2026-08-22 ### BU Robotics Club https://terrierintelligence.com/clubs/bu-robotics-club A student organization focused on building autonomous robots, with mechanical, electrical, and perception teams that bridge classroom theory with hands-on engineering projects. - Topics: Robotics, Computer Vision, ML Theory - Application status: Apply Later - Website: https://www.bu.edu/eng/student-engagement-careers/student-engagement/student-clubs-organizations/bu-robotics-club/ - Last verified: 2026-08-22 ### Sports Analytics Group at BU https://terrierintelligence.com/clubs/bu-sports-analytics-club A student organization focused on sports analytics, bringing statistics enthusiasts together for collaborative projects, research, and events with industry speakers. - Topics: Data Science, Statistics, ML Theory - Meets: Regular projects and events - Application status: Apply Later - Instagram: @bu_sportsanalytics - Contact: busportsanalytics@gmail.com - Last verified: 2026-08-22 ### Kappa Theta Pi (KTP) https://terrierintelligence.com/clubs/kappa-theta-pi-ktp A student organization structured as a professional technology fraternity, drawing students from all majors and centered on career preparation in technology. - Topics: Generative AI/Tools, Data Science - Meets: Chapter events and projects - Application status: Apply Later - Website: https://www.ktp-bostonu.com/ - Instagram: @ktpbostonu - Contact: rcheng86@bu.edu - Last verified: 2026-09-11 ### Robotics & Ambient Intelligence Labs (RAILS) https://terrierintelligence.com/clubs/robotics-ambient-intelligence-labs-rails A student organization focused on robotics and ambient intelligence, the study of environments that sense and respond to the people in them. - Topics: Robotics, HCI, Computer Vision - Application status: Apply Later - Contact: devb@bu.edu - Last verified: 2026-08-22 ### INSTEP (Interface of Science, Technology, Engineering & Policy) https://terrierintelligence.com/clubs/instep A student organization exploring where science and engineering meet public policy, equipping STEM students to engage in policy, regulation, and advocacy work. - Topics: Policy, Ethics, Healthcare - Meets: General body meetings and events each semester - Application status: Applications Open - Website: https://linktr.ee/instep.bu1 - Instagram: @instep.bu - Contact: instep.bu@gmail.com - Last verified: 2026-09-15 --- ## Classes (81) AI-related courses. Offered status refers to Fall 2026. ### PH 272 — Science, Technology, & Values https://terrierintelligence.com/classes/ph-272 An introductory philosophy course examining how science, technology, and society shape human values, and how values in turn shape technical practice. Through case studies of computing, military, and biological technologies, students practice analyzing the social and moral challenges these fields raise. - Course code: PH 272 - Department: CAS - Level: intro - Topics: Ethics - Credits: 4 - Offered: offered - Last verified: 2026-08-22 ### CS 505 — Introduction to Natural Language Processing https://terrierintelligence.com/classes/cs-505 An introductory course on natural language processing, the subfield of AI that aims to give computers the ability to work with human language. Students examine statistical and machine learning techniques for analyzing language data automatically and study how these methods support intelligent language processing. - Course code: CS 505 - Department: CAS - Level: grad - Topics: NLP/LLMs - Credits: 4 - Offered: not_offered - Prerequisites: CS 365 or (CS 440 & MA 225) - Last verified: 2026-08-22 ### CS 506 — Data Science Tools and Applications https://terrierintelligence.com/classes/cs-506 An applied course that builds practical skills for working with data. Students survey a wide range of techniques commonly used in data analysis, including clustering, classification, and regression, and practice each one hands-on by implementing and running it in code. - Course code: CS 506 - Department: CAS - Level: grad - Topics: Data Science - Credits: 4 - Offered: offered - Prerequisites: CS 108/111; CS 132 or MA 242/442 - Last verified: 2026-08-22 ### CS 523 — Deep Learning https://terrierintelligence.com/classes/cs-523 An advanced course on deep neural networks, from feed-forward models, backpropagation, and training strategies to convolutional, recurrent, and transformer architectures. Students also study deep reinforcement and unsupervised learning while gaining hands-on experience with the programming frameworks and libraries used in current practice. - Course code: CS 523 - Department: CAS - Level: grad - Topics: ML Theory, Computer Vision, Generative AI/Tools - Credits: 4 - Offered: not_offered - Cross-listed as: EC 523 - Prerequisites: CS 541 or CS 542 - Last verified: 2026-08-22 ### CS 541 — Applied Machine Learning https://terrierintelligence.com/classes/cs-541 An applied course that develops practical machine learning skills through sustained programming on real-world datasets. Students build and evaluate models using techniques for classification, regression, and clustering, and study feature selection and model compression as ways to make those models leaner. - Course code: CS 541 - Department: CAS - Level: grad - Topics: ML Theory, Data Science - Credits: 4 - Offered: offered - Prerequisites: CS 111/112; CS 132 or MA 242; CS 237 or MA 581 - Last verified: 2026-08-22 ### CS 542 — Principles of Machine Learning https://terrierintelligence.com/classes/cs-542 A foundational course on the concepts and algorithms behind modern machine learning. Students study methods such as regression, support vector machines, and Bayesian networks, then carry the theory into practice through programming assignments that apply each technique to real-world datasets. - Course code: CS 542 - Department: CAS - Level: grad - Topics: ML Theory - Credits: 4 - Offered: offered - Prerequisites: CS 365 - Last verified: 2026-08-22 ### CS 543 — Algorithmic Techniques for Taming Big Data https://terrierintelligence.com/classes/cs-543 An advanced algorithms course on computing with datasets too large to process directly. Students analyze reduction techniques such as sampling, sketching, and dimensionality reduction, plus MapReduce-style protocols for data distributed across machines, then benchmark these methods on public datasets through programming assignments and a final project. - Course code: CS 543 - Department: CAS - Level: grad - Topics: Data Science - Credits: 4 - Offered: not_offered - Prerequisites: Basic data structures and algorithms - Last verified: 2026-08-22 ### CS 549 — Spark! Machine Learning X-Lab Practicum https://terrierintelligence.com/classes/cs-549 A project-based practicum in which students apply skills in algorithms, data analytics, and software development to real projects from BU and external partner organizations. Each student completes an applied machine learning or inferential analytics project, practices communication and project management along the way, and presents final results to the partner. - Course code: CS 549 - Department: CAS - Level: grad - Topics: ML Theory, Data Science - Credits: 4 - Offered: offered - Cross-listed as: DS 549 - Prerequisites: CS 505 or CS 542 or CS 585 - Last verified: 2026-08-22 ### CS 565 — Algorithmic Data Mining https://terrierintelligence.com/classes/cs-565 An algorithms-focused introduction to data mining, the extraction of useful patterns from large datasets. Students examine techniques for discovering associations and correlations, classifying and clustering data at scale, and detecting outliers, treating each method's algorithmic foundations alongside its application to real-world problems. - Course code: CS 565 - Department: CAS - Level: grad - Topics: Data Science - Credits: 4 - Offered: not_offered - Prerequisites: CS 112 & 330 & 365 - Last verified: 2026-08-22 ### CS 585 — Image and Video Computing https://terrierintelligence.com/classes/cs-585 A course on how computers derive understanding from images and video, treating them as multimedia data and analyzing cues such as color, shading, and motion. Students study the algorithms behind applications including face recognition, human-computer interfaces, and medical image analysis. - Course code: CS 585 - Department: CAS - Level: grad - Topics: Computer Vision - Credits: 4 - Offered: not_offered - Prerequisites: CS 132 or MA 242; CS 112 - Last verified: 2026-08-22 ### CS 640 — Artificial Intelligence https://terrierintelligence.com/classes/cs-640 A survey course on building computer systems that behave intelligently, with particular attention to machines that perceive their surroundings and act on them. Students examine core areas such as game playing, knowledge representation, and planning, along with pattern recognition and interfaces between humans and computers. - Course code: CS 640 - Department: CAS - Level: grad - Topics: Computer Vision, Robotics - Credits: 4 - Offered: offered - Prerequisites: CS 330; CS 132 or MA 242 - Last verified: 2026-08-22 ### MET CS 767 — Advanced Machine Learning and Neural Networks https://terrierintelligence.com/classes/met-cs-767 An advanced course on learning from data, moving from supervised and unsupervised fundamentals through neural networks to transformers and attention mechanisms. Students also study adversarial learning, Bayesian methods, and genetic algorithms, and each designs and completes an individual term project applying the material. - Course code: MET CS 767 - Department: MET - Level: grad - Topics: ML Theory, Generative AI/Tools - Credits: 4 - Offered: offered - Prerequisites: MET CS 521 & one of 577/622/673/682 - Last verified: 2026-08-22 ### MET CS 664 — Artificial Intelligence https://terrierintelligence.com/classes/met-cs-664 A broad course on the ideas and techniques that make intelligent behavior possible in computers, including search, reasoning, and knowledge representation. Students examine frameworks for building modern intelligent agents and gain hands-on laboratory practice with methods drawn from machine learning, language processing, and visual perception. - Course code: MET CS 664 - Department: MET - Level: grad - Topics: ML Theory, NLP/LLMs - Credits: 4 - Offered: offered - Prerequisites: MET CS 526 or MET CS 673 - Last verified: 2026-08-22 ### EC 414 — Introduction to Machine Learning https://terrierintelligence.com/classes/ec-414 An introductory course in machine learning covering linear regression, maximum likelihood estimation, and classification methods such as logistic regression, naive Bayes, and support vector machines. Students also practice clustering, data visualization, and dimensionality reduction with principal components analysis, ending with a first treatment of neural networks and deep learning. - Course code: EC 414 - Department: ENG - Level: advanced - Topics: ML Theory - Credits: 4 - Offered: offered - Last verified: 2026-08-22 ### EC 418 — Introduction to Reinforcement Learning https://terrierintelligence.com/classes/ec-418 An introductory course in reinforcement learning, the branch of AI in which agents learn from repeated interaction with an environment. Students study Markov decision processes, dynamic programming, and value and policy iteration, then extend these ideas through temporal-difference methods, Monte Carlo techniques, and function approximation with neural networks. - Course code: EC 418 - Department: ENG - Level: advanced - Topics: ML Theory, Robotics - Credits: 4 - Offered: not_offered - Prerequisites: MA225+EK103+EK381 or DS120/121/122 - Last verified: 2026-08-22 ### EC 503 — Introduction to Learning from Data https://terrierintelligence.com/classes/ec-503 An introductory course in classical machine learning that develops the principles behind four core problems: classification and regression in supervised learning, and clustering and dimensionality reduction in unsupervised learning. Students apply these methods to contemporary applications through problem sets and a course project. - Course code: EC 503 - Department: ENG - Level: grad - Topics: ML Theory, Statistics - Credits: 4 - Offered: offered - Last verified: 2026-08-22 ### EC 523 — Deep Learning https://terrierintelligence.com/classes/ec-523 An advanced course on deep learning, building from feed-forward networks, backpropagation, and training strategies for deep networks to convolutional networks, recurrent networks, and transformers. Students also study diffusion models and deep unsupervised learning, gaining hands-on exposure to PyTorch and other contemporary tools. - Course code: EC 523 - Department: ENG - Level: grad - Topics: ML Theory, Computer Vision, Generative AI/Tools - Credits: 4 - Offered: offered - Cross-listed as: CS 523 - Last verified: 2026-08-22 ### EC 525 — Optimization for Machine Learning https://terrierintelligence.com/classes/ec-525 An advanced course on the optimization algorithms that make training large ML models on large datasets feasible. Students analyze convergence of first-order methods such as stochastic gradient descent, focus on the non-convex losses common in deep learning, and practice reading, designing, and implementing optimization algorithms from the research literature. - Course code: EC 525 - Department: ENG - Level: grad - Topics: ML Theory - Credits: 4 - Offered: not_offered - Last verified: 2026-08-22 ### CS 365 — Foundations of Data Science https://terrierintelligence.com/classes/cs-365 A foundational course preparing students for advanced data-intensive classes in data science, machine learning, and data mining. Students develop the fundamental concepts these fields rest on, treating both the underlying theory and the practical implications of putting it to work on data problems. - Course code: CS 365 - Department: CS - Level: intermediate - Topics: Data Science, Statistics - Credits: 4 - Offered: offered - Prerequisites: CS 112 & 131 & 132 & 237 - Last verified: 2026-08-22 ### CS 440 — Introduction to Artificial Intelligence https://terrierintelligence.com/classes/cs-440 An introductory course on designing computer systems that act intelligently, with particular attention to perceptual and robotic systems. Students examine topics such as computer vision, game playing, and human-computer interfaces, and study how machines recognize patterns, represent knowledge, and plan. - Course code: CS 440 - Department: CS - Level: advanced - Topics: Computer Vision, Robotics - Credits: 4 - Offered: offered - Prerequisites: CS 112 & CS 132 - Last verified: 2026-08-22 ### CS 391 — Responsible AI (Topics in CS) https://terrierintelligence.com/classes/cs-391 A topics course examining how mathematical methods can formally capture societal concerns raised by data-driven systems, including data privacy, algorithmic fairness, and the interpretation of complex ML models. Students combine programming and theoretical problem sets with reading, discussing, and writing about policy and ethics papers. - Course code: CS 391 - Department: CS - Level: intermediate - Topics: AI Safety, Ethics, Policy, Security - Credits: 4 - Offered: not_offered - Prerequisites: CS 237/DS 122; CS 330/DS 320; CS 365/DS 340 - Last verified: 2026-08-22 ### DS 320 — Algorithms for Data Science https://terrierintelligence.com/classes/ds-320 An algorithms course grounding classical design methods, including greedy strategies, divide and conquer, and dynamic programming, in data science applications. Students then study methods suited to large or streaming datasets, where repeated scans are infeasible, practicing with approximation and randomized algorithms designed for efficiency at scale. - Course code: DS 320 - Department: CDS - Level: intermediate - Topics: Data Science - Credits: 4 - Offered: offered - Prerequisites: DS 121 & DS 210 - Last verified: 2026-08-22 ### DS 340 — Introduction to Machine Learning and AI https://terrierintelligence.com/classes/ds-340 An introductory course spanning core AI and ML algorithms, from search and probabilistic reasoning to neural networks and transformer architectures. Students build conceptual understanding through applications such as image classification, sentiment analysis, and recommender systems, then bring the ideas together in a final project. - Course code: DS 340 - Department: CDS - Level: intermediate - Topics: ML Theory, Data Science - Credits: 4 - Offered: offered - Prerequisites: DS 122 & DS 320 - Last verified: 2026-08-22 ### DS 380 — Data, Society, and AI Ethics https://terrierintelligence.com/classes/ds-380 A course on how AI and data-driven technologies shape society and public policy, and how policy shapes them in turn. Students practice with established ethics tools and analyze real-world case studies, pairing each case with a relevant ethical framework to reason about emerging ethical challenges. - Course code: DS 380 - Department: CDS - Level: intermediate - Topics: Ethics, Policy - Credits: 4 - Offered: not_offered - Last verified: 2026-08-22 ### CS 531 — Advanced Optimization Algorithms https://terrierintelligence.com/classes/cs-531 An advanced course on optimization algorithms that highlights the interplay between discrete and continuous methods. Students study gradient descent, online optimization, and linear and semidefinite programming with duality, and examine network optimization, submodular optimization, and approximation algorithms built on continuous relaxations. - Course code: CS 531 - Department: CS - Level: grad - Topics: ML Theory - Credits: 4 - Offered: offered - Prerequisites: MA 123 & 124; CS 132 - Last verified: 2026-08-22 ### CS 561 — Data Systems Architectures https://terrierintelligence.com/classes/cs-561 An advanced course on designing data systems that manage large, growing, and diverse datasets, often streaming from heterogeneous sources, atop continually evolving hardware. Students draw examples from relational and distributed databases, key-value and NoSQL stores, and systems that support machine learning and that use ML to tune themselves. - Course code: CS 561 - Department: CS - Level: grad - Topics: Data Science - Credits: 4 - Offered: not_offered - Prerequisites: CS 210; CS 460/660 - Last verified: 2026-08-22 ### EC 518 — Robot Learning https://terrierintelligence.com/classes/ec-518 An advanced course examining how robots learn to perceive and act, combining machine perception with decision-making algorithms. Students study 3D vision, reinforcement and imitation learning, and model-based approaches, and analyze problems such as exploration and human-robot interaction through both theory and experiment. - Course code: EC 518 - Department: ENG - Level: grad - Topics: ML Theory, Robotics, Computer Vision - Credits: 4 - Offered: offered - Prerequisites: MA 225, EK 103, EK 381, EK 128, EC 414 - Last verified: 2026-08-22 ### EC 519 — Speech Processing by Humans and Machines https://terrierintelligence.com/classes/ec-519 An advanced course examining how humans produce and perceive speech and how machines represent it. Students build foundations in speech production, perception, and signal processing, then apply signal-processing methods for analyzing speech signals, the basis for speech-controlled interaction between people and machines. - Course code: EC 519 - Department: ENG - Level: grad - Topics: NLP/LLMs, HCI - Credits: 4 - Offered: not_offered - Prerequisites: EK 381; BE 401 or EC 401; MATLAB - Last verified: 2026-08-22 ### EC 524 — Optimization Theory and Methods https://terrierintelligence.com/classes/ec-524 An advanced course on formulating and solving optimization problems, covering the mathematical structures behind linear, integer, and nonlinear programming. Students practice methods such as the simplex algorithm, interior-point techniques, and gradient-based approaches, and apply them to case studies in planning, routing, and scheduling. - Course code: EC 524 - Department: ENG - Level: grad - Topics: ML Theory - Credits: 4 - Offered: offered - Prerequisites: EK 103 or MA 142 - Last verified: 2026-08-22 ### ME 570 — Robot Motion Planning https://terrierintelligence.com/classes/me-570 An advanced course on algorithms that plan how a robot moves through its environment, grounded in the topology of configuration spaces. Students examine potential functions, roadmaps, and cell decompositions, then study sampling-based planners and model-checking approaches to robot motion planning and control. - Course code: ME 570 - Department: ENG - Level: grad - Topics: Robotics - Credits: 4 - Offered: offered - Prerequisites: MA 226, EK 103, EK 121/125 - Last verified: 2026-08-22 ### MA 751 — Statistical Machine Learning https://terrierintelligence.com/classes/ma-751 An advanced course examining machine learning from a statistical perspective, treating learning methods as models that are fit to data and evaluated for how well they generalize. Coursework centers on the statistical theory that underlies how such learning algorithms behave. - Course code: MA 751 - Department: Math - Level: grad - Topics: ML Theory, Statistics - Credits: 4 - Offered: not_offered - Prerequisites: MA 575 & MA 581 - Last verified: 2026-08-22 ### MA 569 — Optimization Methods of Operations Research https://terrierintelligence.com/classes/ma-569 An advanced course on optimizing linear and nonlinear functions, spanning linear programming and the simplex method through Lagrange multipliers and Kuhn-Tucker conditions. Students practice formulating and solving transportation, assignment, and network problems, and study constrained optima, the calculus of variations, and Euler's equation. - Course code: MA 569 - Department: Math - Level: grad - Topics: ML Theory - Credits: 4 - Offered: offered - Prerequisites: MA 225 & MA 242 - Last verified: 2026-08-22 ### MA 589 — Computational Statistics https://terrierintelligence.com/classes/ma-589 An advanced course on the computational techniques behind modern statistical practice, from random number generation and sampling to Markov chain Monte Carlo methods. Students apply Monte Carlo simulation, graphical models, and bootstrapping to build conceptual understanding of computational inference through concrete applications. - Course code: MA 589 - Department: CAS - Level: grad - Topics: Statistics, Data Science - Credits: 4 - Offered: not_offered - Prerequisites: MA 575 - Last verified: 2026-08-22 ### MA 592 — Introduction to Causal Inference https://terrierintelligence.com/classes/ma-592 An advanced course examining what justifies a causal claim when association alone does not. Students study concepts and methods for estimating causal effects from data, applying them in experimental settings and in non-experimental settings where controlled randomization of treatments is unavailable. - Course code: MA 592 - Department: Math - Level: grad - Topics: Statistics, Data Science - Credits: 4 - Offered: not_offered - Prerequisites: MA 575 - Last verified: 2026-08-22 ### DS 381 — Social Justice for Data Science https://terrierintelligence.com/classes/ds-381 A course examining how AI systems trained on large datasets shape decisions in domains such as criminal justice, housing, and healthcare, and how they can reinforce racial, class, and gender subordination. Students practice identifying these harms and analyzing the data practices, computational techniques, and policy choices behind them. - Course code: DS 381 - Department: CDS - Level: intermediate - Topics: Ethics, Policy - Credits: 4 - Offered: offered - Last verified: 2026-08-22 ### DS 457 — Law for Algorithms https://terrierintelligence.com/classes/ds-457 An interdisciplinary course connecting computer-science concepts such as proof, verifiability, and privacy with legal concepts such as consent, governance, and liability. Students from law and computing backgrounds write weekly reflections and complete a collaborative final project in mixed teams, examining how algorithms reshape social processes. - Course code: DS 457 - Department: CDS - Level: advanced - Topics: Ethics, Policy, Security - Credits: 4 - Offered: not_offered - Prerequisites: DS 122 & DS 320 - Last verified: 2026-08-22 ### DS 482 — Responsible AI, Law, Ethics & Society https://terrierintelligence.com/classes/ds-482 An advanced course examining the challenges that arise when AI systems are deployed across societal domains, including accountability, fairness, and privacy. Students from computing, law, and public-policy backgrounds work through principles and practices drawn from data science, ethics, and law. - Course code: DS 482 - Department: CDS - Level: advanced - Topics: AI Safety, Ethics, Policy - Credits: 4 - Offered: not_offered - Prerequisites: DS 100/110 & DS 340 - Last verified: 2026-08-22 ### DS 522 — Stochastic Methods for Algorithms https://terrierintelligence.com/classes/ds-522 An advanced course using the theory of stochastic processes to understand why algorithms in statistics and ML work, with emphasis on Markov chain Monte Carlo and stochastic optimization. Students practice linking theory to computational behavior through proofs, numerical experiments, and expository writing. - Course code: DS 522 - Department: CDS - Level: grad - Topics: ML Theory - Credits: 4 - Offered: offered - Prerequisites: DS 122; MA 581/CS 237/EK 381 - Last verified: 2026-08-22 ### DS 542 — Deep Learning for Data Science https://terrierintelligence.com/classes/ds-542 An advanced course grounding students in deep learning fundamentals — loss functions, gradient descent, backpropagation — and the architectures built on them, from convolutional networks to transformers. Students build, train, and evaluate models in PyTorch, gain exposure to pre-trained foundation models, and apply the material in a final project. - Course code: DS 542 - Department: CDS - Level: grad - Topics: ML Theory, Generative AI/Tools, Computer Vision - Credits: 4 - Offered: not_offered - Last verified: 2026-08-22 ### DS 543 — Introduction to Reinforcement Learning https://terrierintelligence.com/classes/ds-543 An introductory course on reinforcement learning that keeps the mathematics deliberately light, building up from Markov decision processes to the field's main algorithmic families: model-based, value-based, and policy-based learning. Students also examine modern challenges and open problems that shape current reinforcement-learning research. - Course code: DS 543 - Department: CDS - Level: grad - Topics: ML Theory, Robotics - Credits: 4 - Offered: not_offered - Last verified: 2026-08-22 ### BA 476 — Machine Learning for Business Analytics https://terrierintelligence.com/classes/ba-476 A foundational course in machine learning for business, drawing on statistics, linear algebra, and optimization to explain why algorithms work, when they fail, and how they create value. Students practice training models in Python and deriving insights and predictions from real-world business data. - Course code: BA 476 - Department: Questrom - Level: advanced - Topics: ML Theory, Data Science - Credits: 4 - Offered: not_offered - Prerequisites: Junior standing; CS 108/111 or DS 110 or BA 222 - Last verified: 2026-08-22 ### CS 581 — Computational Fabrication https://terrierintelligence.com/classes/cs-581 An advanced course on computational fabrication that pairs 3D printing technology with the computational methods used to turn geometric models into physical prototypes. Students present recent research from computer graphics and human-computer interaction venues and complete a design project combining computation with physical prototyping. - Course code: CS 581 - Department: CS - Level: grad - Topics: HCI - Credits: 4 - Offered: not_offered - Last verified: 2026-08-22 ### LX 496 — Introduction to Computational Linguistics https://terrierintelligence.com/classes/lx-496-introduction-to-computational-linguistics An introductory course in computational linguistics that applies algorithms, data structures, and tool libraries to explore linguistic models and test empirical claims about language. Students practice core tasks such as tagging and classification, parsing, and meaning representation, along with corpus creation and information extraction. - Course code: LX 496 - Department: CAS - Level: advanced - Topics: NLP/LLMs, ML Theory - Credits: 4 - Offered: not_offered - Prerequisites: See bulletin - Bulletin: https://www.bu.edu/academics/cas/programs/linguistics/ba-in-linguistics-computer-science/ - Last verified: 2026-08-22 ### WR 250 — AI Literacy for Writing https://terrierintelligence.com/classes/wr-250-ai-literacy-for-writing A writing course that builds a foundational understanding of generative AI and its effects on writing and society. Students experiment with generative tools, weigh ethical questions and real-world applications, and create projects that blend traditional written work with multimodal composition. - Course code: WR 250 - Department: CAS - Level: intermediate - Topics: Generative AI/Tools, Ethics, HCI - Credits: 4 - Typical semester: Both - Offered: offered - Prerequisites: First-Year Writing Seminar and WR 151/152/153 - Bulletin: https://www.bu.edu/academics/cas/courses/cas-wr-250/ - Last verified: 2026-08-22 ### CM 509 — Digital Deception: AI, Deepfakes and Deceiving by Design https://terrierintelligence.com/classes/cm-509-digital-deception-ai-deepfakes-and-deceiving-by-design A course examining how AI-generated media and deepfakes reshape what audiences can trust, tracing how misinformation is engineered, amplified, and weaponized across platforms. Students study the psychology of susceptibility and practice evaluating synthetic content and building countermeasures for work in media, marketing, and communication. - Course code: CM 509 - Department: COM - Level: advanced - Topics: Generative AI/Tools, Ethics, Policy - Credits: 4 - Typical semester: Fall - Offered: not_offered - Bulletin: https://www.bu.edu/academics/com/courses/2/ - Last verified: 2026-08-22 ### CM 626 — AI and New Technologies https://terrierintelligence.com/classes/cm-626-ai-and-new-technologies An introductory course on planning, applying, and evaluating integrated communication in the AI era, moving from traditional content distribution toward managing autonomous and generative systems. Students work through AI fundamentals and multimodal content generation, culminating in vibe coding and agentic-system orchestration. - Course code: CM 626 - Department: COM - Level: grad - Topics: Generative AI/Tools, HCI, Ethics - Credits: 4 - Offered: not_offered - Bulletin: https://www.bu.edu/academics/com/courses/4/ - Last verified: 2026-08-22 ### EK 505 — Introduction to Robotics https://terrierintelligence.com/classes/ek-505-introduction-to-robotics An introductory course laying the foundation for robotics and autonomous systems, covering how to model manipulator arms, vehicles, and soft robots. Students study control and motion planning, sensing and perception, and machine learning applications in robotics, alongside the ethical implications of increasingly commonplace automation. - Course code: EK 505 - Department: ENG - Level: grad - Topics: Robotics, Computer Vision, ML Theory - Credits: 4 - Offered: offered - Prerequisites: Graduate standing - Bulletin: https://www.bu.edu/academics/eng/programs/mechanical-engineering/ms-in-robotics-autonomous-systems/ - Last verified: 2026-08-22 ### ME 416 — Introduction to Robotics https://terrierintelligence.com/classes/me-416-introduction-to-robotics An introductory course pairing robotics theory with hands-on building, covering how robots are modeled and controlled and how they perceive, map, and plan within physical environments. The course culminates with students constructing a simple but complete robotic system that competes against their classmates' designs. - Course code: ME 416 - Department: ENG - Level: advanced - Topics: Robotics, Computer Vision, ML Theory - Credits: 4 - Typical semester: Both - Offered: offered - Prerequisites: ME 302, EC 327, EC 401, or BE 403 - Bulletin: https://www.bu.edu/academics/eng/courses/eng-me-416/ - Last verified: 2026-08-22 ### ME 568 — Soft Robotic Technologies https://terrierintelligence.com/classes/me-568-soft-robotic-technologies An advanced course on soft robotics and the unconventional actuation and sensing technologies that distinguish it from rigid systems, spanning shape-memory alloys, soft fluidic actuators, and flexible sensors. Substantial hands-on experimental work lets students practice the design, manufacture, and control of functional soft robotic devices. - Course code: ME 568 - Department: ENG - Level: grad - Topics: Robotics, Healthcare - Credits: 4 - Offered: not_offered - Prerequisites: See bulletin - Bulletin: https://www.bu.edu/eng/academics/explore-degree-programs/concentration-in-robotics/ - Last verified: 2026-08-22 ### ME 571 — Medical Robotics https://terrierintelligence.com/classes/me-571-medical-robotics An advanced course on the design, mechanics, and control of robots built for medical applications, from meso-scale actuators and sensors to complete mechatronic systems. Students combine theory with case studies drawn from medical companies and research groups, working through design problems in tutorials and group work. - Course code: ME 571 - Department: ENG - Level: grad - Topics: Robotics, Healthcare, Computer Vision - Credits: 4 - Typical semester: Spring - Offered: offered - Prerequisites: See bulletin - Bulletin: https://www.bu.edu/eng/files/2025/08/Robotics-Autonomous-Systems-Spring-2026-Grad-Courses-One-Pager-Fall-2025.pdf - Last verified: 2026-08-22 ### JD 794 — Artificial Intelligence Law https://terrierintelligence.com/classes/jd-794-artificial-intelligence-law A course examining the emerging law, regulation, and policy governing AI systems, covering questions of liability, privacy, and intellectual property alongside bias, explainability, and governance. Students also practice AI-assisted lawyering, using large language models on case studies while probing their hallucinations, opacity, and professional-responsibility risks. - Course code: JD 794 - Department: LAW - Level: grad - Topics: Policy, Ethics, Generative AI/Tools - Credits: 3 - Typical semester: Spring - Offered: not_offered - Prerequisites: JD enrollment - Bulletin: https://www.bu.edu/academics/law/courses/law-jd-794/ - Last verified: 2026-08-22 ### MET AD 698 — Applied Generative AI for Business Analytics https://terrierintelligence.com/classes/met-ad-698-applied-generative-ai-for-business-analytics An applied course in building production-ready generative AI systems for business problems, moving from prompt engineering and retrieval-augmented generation to fine-tuning and deployment. Students practice with frameworks such as LangChain and LlamaIndex while designing agentic applications grounded in responsible-AI principles. - Course code: MET AD 698 - Department: MET - Level: grad - Topics: Generative AI/Tools, NLP/LLMs, Data Science - Credits: 4 - Typical semester: Fall - Offered: offered - Prerequisites: Corequisite MET AD 100 Lab - Bulletin: https://www.bu.edu/academics/met/courses/met-ad-698/ - Last verified: 2026-08-22 ### MET CS 766 — Deep Reinforcement Learning https://terrierintelligence.com/classes/met-cs-766-deep-reinforcement-learning An advanced course examining reinforcement learning from Markov decision processes and multi-armed bandits to deep neural approaches. Students practice tabular methods such as Monte Carlo, temporal-difference learning, and Q-learning, then build deep Q-network, policy-gradient, and actor-critic agents, with attention to safety and ethical issues. - Course code: MET CS 766 - Department: MET - Level: grad - Topics: ML Theory, Robotics, AI Safety - Credits: 4 - Typical semester: Both - Offered: offered - Prerequisites: MET CS 767 or consent - Bulletin: https://www.bu.edu/met/degrees-certificates/ms-applied-data-analytics-ai-machine-learning/ - Last verified: 2026-08-22 ### MET CS 788 — Generative AI https://terrierintelligence.com/classes/met-cs-788-generative-ai An advanced course that builds from statistical and neural-network foundations, including regression, optimization, and transformer architectures, toward generative modeling. Students examine autoencoders, generative adversarial networks, and large language models, then study image and 3D synthesis methods such as text-to-image models and Gaussian splatting. - Course code: MET CS 788 - Department: MET - Level: grad - Topics: Generative AI/Tools, NLP/LLMs, Computer Vision - Credits: 4 - Typical semester: Both - Offered: offered - Prerequisites: MET CS 577 plus Python, ML math, and neural networks - Bulletin: https://www.bu.edu/academics/met/courses/met-cs-788/ - Last verified: 2026-08-22 ### BA 510 — Neural Networks and AI: From Foundations to Generative Models https://terrierintelligence.com/classes/ba-510-neural-networks-and-ai-from-foundations-to-generative-models An applications-focused course that introduces neural networks, tracing them from the most basic formulations to contemporary generative AI architectures. Students implement and train models in TensorFlow and Keras, gaining hands-on practice with diverse data types that include images, text, and audio. - Course code: BA 510 - Department: Questrom - Level: advanced - Topics: ML Theory, Generative AI/Tools, Computer Vision, NLP/LLMs - Credits: 4 - Offered: not_offered - Prerequisites: QST BA 222 or BA 223 - Bulletin: https://www.bu.edu/academics/questrom/courses/qst-ba-510/ - Last verified: 2026-08-22 ### BA 576 — Machine Learning for Business Analytics https://terrierintelligence.com/classes/ba-576-machine-learning-for-business-analytics An introductory course on the machine learning techniques reshaping business practice, grounding algorithms in statistics, linear algebra, and optimization. Students examine when algorithms succeed or fail and how they generate business value, then practice training models in Python and drawing predictions from real-world data. - Course code: BA 576 - Department: Questrom - Level: advanced - Topics: ML Theory, Data Science - Credits: 4 - Typical semester: Both - Offered: offered - Cross-listed as: BA 476 - Prerequisites: CAS CS 108/111, CDS DS 110, or QST BA 222 - Bulletin: https://www.bu.edu/academics/questrom/courses/qst-ba-576/ - Last verified: 2026-08-22 ### BA 810 — Supervised Machine Learning https://terrierintelligence.com/classes/ba-810-supervised-machine-learning An applied course on supervised machine learning and its business uses, taught through lectures and in-class exercises. Students practice building predictive models in Python on real-world datasets drawn largely from digital interactions, working toward actionable business insights and clear presentation of findings. - Course code: BA 810 - Department: Questrom - Level: grad - Topics: ML Theory, Data Science - Credits: 3 - Typical semester: Fall - Offered: offered - Prerequisites: QST BA 600, 602, 780 - Bulletin: https://www.bu.edu/academics/questrom/courses/qst-ba-810/ - Last verified: 2026-08-22 ### BA 820 — Unsupervised and Unstructured Machine Learning https://terrierintelligence.com/classes/ba-820-unsupervised-and-unstructured-machine-learning An applied course on machine learning for data that lacks labels or predefined structure, which makes up most of the information organizations hold. Students compare contemporary methods through lectures and practical exercises, practicing how to extract business insight from datasets with no known outcome variable. - Course code: BA 820 - Department: Questrom - Level: grad - Topics: ML Theory, NLP/LLMs, Data Science - Credits: 3 - Typical semester: Spring - Offered: not_offered - Prerequisites: QST BA 600, 602, 780, 810 - Bulletin: https://www.bu.edu/academics/questrom/courses/qst-ba-820/ - Last verified: 2026-08-22 ### BA 882 — Deploying Analytics Pipelines https://terrierintelligence.com/classes/ba-882-deploying-analytics-pipelines An applied course on moving analytics and machine learning into production on cloud platforms. Students build and deploy data and ML pipelines, practicing extract-transform-load processes, data-quality monitoring, and serving models as APIs, with coverage of cloud warehousing, machine-learning operations, and generative AI applications. - Course code: BA 882 - Department: Questrom - Level: grad - Topics: Data Science, Generative AI/Tools - Credits: 3 - Typical semester: Fall - Offered: offered - Prerequisites: QST BA 600, 602, 780, 810, 820 - Bulletin: https://www.bu.edu/academics/questrom/courses/qst-ba-882/ - Last verified: 2026-08-22 ### IS 813 — Generative AI: Implementation and Impact for Business https://terrierintelligence.com/classes/is-813-generative-ai-implementation-and-impact-for-business A hands-on course on putting generative AI to work in business settings. Students practice fine-tuning, prompt engineering, and deployment strategies with language models such as GPT through interactive sessions and real-world projects, and examine responsible-use issues including privacy, bias, and hallucinated outputs. - Course code: IS 813 - Department: Questrom - Level: grad - Topics: Generative AI/Tools, Ethics, AI Safety - Credits: 1.5 - Offered: not_offered - Prerequisites: Minimal coding experience expected - Bulletin: https://www.bu.edu/academics/questrom/courses/qst-is-813/ - Last verified: 2026-08-22 ### IS 863 — Integration of Generative AI in Business Practice https://terrierintelligence.com/classes/is-863-integration-of-generative-ai-in-business-practice A strategy-focused course on implementing generative AI across an organization, taught without programming through lectures, case studies, and exercises. Students practice prioritizing applications, drafting integration roadmaps, and weighing legal, intellectual-property, and ethical issues, drawing on practitioner accounts of adoption barriers inside major companies. - Course code: IS 863 - Department: Questrom - Level: grad - Topics: Generative AI/Tools, Policy, Ethics - Credits: 1.5 - Offered: not_offered - Bulletin: https://www.bu.edu/academics/questrom/courses/qst-is-865/ - Last verified: 2026-08-22 ### IS 883 — Deploying Generative AI in the Enterprise https://terrierintelligence.com/classes/is-883-deploying-generative-ai-in-the-enterprise An applied course on bringing large language models into enterprise use. Students examine how the models are structured and operate, practice integration through Azure and OpenAI interfaces along with prompt engineering, and close by architecting an AI-driven business project that combines technical deployment with strategic and ethical considerations. - Course code: IS 883 - Department: Questrom - Level: grad - Topics: Generative AI/Tools, NLP/LLMs, Ethics - Credits: 3 - Typical semester: Fall - Offered: offered - Prerequisites: MSDT students only - Bulletin: https://www.bu.edu/academics/questrom/courses/qst-is-883/ - Last verified: 2026-08-22 ### MF 815 — Advanced Machine Learning Applications for Finance https://terrierintelligence.com/classes/mf-815-advanced-machine-learning-applications-for-finance An advanced course surveying machine learning applications across financial datasets. It applies deep and supervised learning to pricing, hedging, and portfolio management, examines clustering, reinforcement learning tied to optimal control, and mining of financial text, and covers strategy backtesting and risk assessment. - Course code: MF 815 - Department: Questrom - Level: grad - Topics: ML Theory, NLP/LLMs, Data Science - Credits: 3 - Typical semester: Spring - Offered: not_offered - Prerequisites: Graduate Certificate in Financial Technology - Bulletin: https://www.bu.edu/academics/questrom/courses/qst-mf-815/ - Last verified: 2026-08-22 ### MF 850 — Deep Learning, Statistical Learning https://terrierintelligence.com/classes/mf-850-deep-learning-statistical-learning An advanced course connecting statistical and machine learning with the numerical methods used to price and hedge financial derivatives. Students examine cross-validation, dimensionality reduction, and clustering alongside neural networks and random forests, together with simulation, optimization, and stochastic models that incorporate jumps. - Course code: MF 850 - Department: Questrom - Level: grad - Topics: ML Theory, Statistics - Credits: 3 - Typical semester: Fall - Offered: offered - Prerequisites: MSMFT restrictions may apply - Bulletin: https://www.bu.edu/academics/questrom/courses/qst-mf-850/ - Last verified: 2026-08-22 ### MK 842 — Machine Learning for Business Analytics https://terrierintelligence.com/classes/mk-842-machine-learning-for-business-analytics An introductory course grounding machine learning for business in statistics, linear algebra, and optimization. Students study how algorithms detect structure in large datasets, where they break down, and how they create business value, while gaining hands-on practice training models in Python on real-world data. - Course code: MK 842 - Department: Questrom - Level: grad - Topics: ML Theory, Data Science - Credits: 3 - Offered: not_offered - Prerequisites: QST MK 723 or MK 724 - Bulletin: https://www.bu.edu/academics/questrom/courses/qst-mk-842/ - Last verified: 2026-08-22 ### MS 777 — AI for Business Challenges https://terrierintelligence.com/classes/ms-777-ai-for-business-challenges A hands-on business course on applying large language models such as GPT to organizational problems. Students practice prompt engineering, model fine-tuning, and deployment strategies through interactive sessions and applied projects, and examine responsible-implementation issues including privacy, bias, and hallucinated outputs. - Course code: MS 777 - Department: Questrom - Level: grad - Topics: Generative AI/Tools, Ethics, AI Safety - Credits: 1.5 - Typical semester: Spring - Offered: not_offered - Prerequisites: Program restrictions may apply - Bulletin: https://www.bu.edu/academics/questrom/courses/qst-ms-777/ - Last verified: 2026-08-22 ### MS 779 — Business Experimentation with AI https://terrierintelligence.com/classes/ms-779-business-experimentation-with-ai A project-driven business course on innovation through iterative experimentation. Students use generative AI and digital tools to develop, test, and refine business solutions in quick, repeated cycles, and practice structured methods for addressing complex organizational problems through collaborative, hands-on assignments. - Course code: MS 779 - Department: Questrom - Level: grad - Topics: Generative AI/Tools, HCI - Credits: 1.5 - Offered: not_offered - Bulletin: https://www.bu.edu/academics/questrom/courses/qst-ms-779/ - Last verified: 2026-08-22 ### AI 601 — Foundations of AI in Educational Contexts https://terrierintelligence.com/classes/ai-601-foundations-of-ai-in-educational-contexts A foundational course for educators on how AI systems work and what they mean for learning. Students examine core AI concepts, ethical questions, and practical classroom applications, and practice making sound, equitable decisions about adopting and communicating AI use in educational settings. - Course code: AI 601 - Department: Wheelock - Level: grad - Topics: Education, Generative AI/Tools, Ethics - Credits: 4 - Offered: offered - Prerequisites: Admission to or approval from the AI & Education program - Bulletin: https://www.bu.edu/academics/wheelock/programs/artificial-intelligence/edm-in-ai-education/ - Last verified: 2026-08-22 ### AI 605 — AI in Teaching and Learning: Pedagogical Applications https://terrierintelligence.com/classes/ai-605-ai-in-teaching-and-learning-pedagogical-applications A methods course for educators on designing instruction that integrates AI tools to strengthen student learning. Students apply learning-sciences and pedagogical principles to plan, deliver, and evaluate AI-supported lessons, with attention to equity, learner agency, and meaningful engagement across varied educational settings. - Course code: AI 605 - Department: Wheelock - Level: grad - Topics: Education, Generative AI/Tools, Ethics - Credits: 4 - Offered: offered - Prerequisites: Admission to or approval from the AI & Education program - Bulletin: https://www.bu.edu/academics/wheelock/programs/artificial-intelligence/edm-in-ai-education/ - Last verified: 2026-08-22 ### AI 620 — AI and Assessment of Student Learning and Experience https://terrierintelligence.com/classes/ai-620-ai-and-assessment-of-student-learning-and-experience A course on the intersection of AI and the assessment of student learning and experience, part of an education curriculum that prepares practitioners to engage with AI critically. It reflects the program's emphasis on ethical practice, bias mitigation, and human-centered use of AI in education. - Course code: AI 620 - Department: Wheelock - Level: grad - Topics: Education, Generative AI/Tools, Ethics - Credits: 4 - Offered: not_offered - Prerequisites: Admission to or approval from the AI & Education program - Bulletin: https://www.bu.edu/academics/wheelock/programs/artificial-intelligence/edm-in-ai-education/ - Last verified: 2026-08-22 ### AI 645 — AI in Education: Historical Perspectives and Design Approaches for Learning https://terrierintelligence.com/classes/ai-645-ai-in-education-historical-perspectives-and-design-approaches-for-learning A course examining how AI in education has developed over time and how design approaches shape learning experiences. Within a curriculum that applies learning-sciences principles to instructional design with AI support, it connects the field's history to present-day design practice. - Course code: AI 645 - Department: Wheelock - Level: grad - Topics: Education, Generative AI/Tools, Ethics - Credits: 4 - Offered: not_offered - Prerequisites: Admission to or approval from the AI & Education program - Bulletin: https://www.bu.edu/academics/wheelock/programs/artificial-intelligence/edm-in-ai-education/ - Last verified: 2026-08-22 ### AI 662 — AI in Educational Data Analytics and Visualization https://terrierintelligence.com/classes/ai-662-ai-in-educational-data-analytics-and-visualization A course on techniques for analyzing and visualizing educational data. Part of an AI and education curriculum, it develops educators' ability to work with learner data, examining patterns, communicating findings visually, and applying the program's emphasis on ethical, critical engagement with AI. - Course code: AI 662 - Department: Wheelock - Level: grad - Topics: Education, Generative AI/Tools, Ethics - Credits: 4 - Offered: not_offered - Prerequisites: Admission to or approval from the AI & Education program - Bulletin: https://www.bu.edu/academics/wheelock/programs/artificial-intelligence/edm-in-ai-education/ - Last verified: 2026-08-22 ### AI 665 — Research Methods and Evidence in Educational AI https://terrierintelligence.com/classes/ai-665-research-methods-and-evidence-in-educational-ai A course on research methods and standards of evidence for AI in education. It prepares educators to read and evaluate studies of AI in teaching and learning, supporting the curriculum's broader aim of critical, evidence-based engagement with AI in educational settings. - Course code: AI 665 - Department: Wheelock - Level: grad - Topics: Education, Generative AI/Tools, Ethics - Credits: 4 - Offered: not_offered - Prerequisites: Admission to or approval from the AI & Education program - Bulletin: https://www.bu.edu/academics/wheelock/programs/artificial-intelligence/edm-in-ai-education/ - Last verified: 2026-08-22 ### AI 695 — AI Implementation and Professional Leadership https://terrierintelligence.com/classes/ai-695-ai-implementation-and-professional-leadership A course on leading AI adoption in educational organizations. Aimed at the program's audience of working professionals, it addresses implementing AI ethically, including bias mitigation, and the leadership work of guiding colleagues, institutions, and policy toward human-centered AI use in education. - Course code: AI 695 - Department: Wheelock - Level: grad - Topics: Education, Generative AI/Tools, Ethics - Credits: 4 - Offered: not_offered - Prerequisites: Admission to or approval from the AI & Education program - Bulletin: https://www.bu.edu/academics/wheelock/programs/artificial-intelligence/edm-in-ai-education/ - Last verified: 2026-08-22 ### AI 699 — AI & Education Research-to-Practice Capstone https://terrierintelligence.com/classes/ai-699-ai-education-research-to-practice-capstone A culminating course in which students complete a capstone project connecting research on AI in education to professional practice. It draws together the curriculum's technical, pedagogical, and critical threads, and students apply earlier coursework in one sustained, practice-oriented final project. - Course code: AI 699 - Department: Wheelock - Level: grad - Topics: Education, Generative AI/Tools, Ethics - Credits: 2 - Offered: not_offered - Prerequisites: Admission to or approval from the AI & Education program - Bulletin: https://www.bu.edu/academics/wheelock/programs/artificial-intelligence/edm-in-ai-education/ - Last verified: 2026-08-22 ### CS 103 — Introduction to Internet Technologies and Web Programming https://terrierintelligence.com/classes/cs-103 An introductory course on how the Internet works, covering its underlying architecture and protocols before moving into web design, web application programming, and algorithmic thinking. - Course code: CS 103 - Department: CAS - Level: intro - Topics: Generative AI/Tools, Education - Credits: 4 - Offered: offered - Bulletin: https://www.bu.edu/academics/cas/courses/cas-cs-103/ - Last verified: 2026-09-04 ### CS 303 — Web Application Development https://terrierintelligence.com/classes/cs-303 An intermediate course in which students build dynamic, full-stack web applications. Work moves through Git and GitHub, HTML and CSS, JavaScript, React, Next.js, and MongoDB, with deployment on Vercel. - Course code: CS 303 - Department: CAS - Level: intermediate - Topics: Generative AI/Tools, Education - Credits: 4 - Offered: offered - Prerequisites: CS 111, CS 112 - Last verified: 2026-09-04 ### CS 598 — Agentic AI for Everything (Topics in CS) https://terrierintelligence.com/classes/cs-598 An advanced topics course on agentic AI systems that reason, plan, and execute multistep workflows. Students study reasoning loops such as ReAct, memory and context management, and tool calling, then implement a personal agent of their own. - Course code: CS 598 - Department: CAS - Level: grad - Topics: Generative AI/Tools, NLP/LLMs, AI Safety - Credits: 4 - Offered: offered - Prerequisites: One of CS 440, CS 505, CS 523, CS 541, or CS 542 with a B+ or higher, or instructor permission - Bulletin: https://www.bu.edu/academics/cas/courses/cas-cs-598/ - Last verified: 2026-09-04 ### HI 393 — Israeli-Palestinian Conflict https://terrierintelligence.com/classes/hi-393 A history course tracing the Israeli-Palestinian conflict and analyzing its competing narratives through primary sources and film. Students present their own reflections and debate possibilities for resolution. - Course code: HI 393 - Department: CAS - Level: intermediate - Topics: Generative AI/Tools, Education, Humanities - Credits: 4 - Offered: offered - Bulletin: https://www.bu.edu/academics/cas/courses/cas-hi-393/ - Last verified: 2026-09-04 ### DS 593 — Theory and Applications of Large Language Models https://terrierintelligence.com/classes/ds-593-large-language-models A Spring 2026 topics course examining transformer architecture, sampling, search, and the critical evaluation of large language models. Students built small models and applied pretrained systems through fine-tuning, prompt engineering, retrieval-augmented generation, and agents, with attention to bias, safety, and responsible deployment. - Course code: DS 593 - Department: CDS - Level: advanced - Topics: NLP/LLMs, Generative AI/Tools, AI Safety - Credits: 4 - Offered: not_offered - Bulletin: https://www.bu.edu/academics/cds/courses/cds-ds-593/ - Last verified: 2026-09-22 ### HUB XC 475 — Spark! Technology Innovation Fellowship https://terrierintelligence.com/classes/hub-xc-475 A one-semester fellowship course in which interdisciplinary student teams take a product from concept to working prototype through Spark!'s structured product innovation process. Teams of technical and design students receive support from Spark! staff and industry mentors, and students may bring their own idea or join a team. - Course code: HUB XC 475 - Department: BU Spark! - Level: advanced - Topics: Generative AI/Tools - Typical semester: Both - Offered: offered - Cross-listed as: CFA AR 675 - Prerequisites: Application, interview, and a technical or design assessment. Technical students need proficiency in a programming language; design students need proficiency in design software. Juniors and seniors get priority, and registration requires department permission. - Syllabus: https://www.bu.edu/spark/students/xc475/ - Last verified: 2026-09-23 --- ## Professors (222) AI-affiliated Boston University faculty. ### Kate Saenko https://terrierintelligence.com/professors/kate-saenko A computer vision researcher who develops adaptive machine learning methods that help deep models generalize across changing data distributions. Her group studies domain adaptation, vision-and-language tasks such as captioning and visual question answering, and bias in multimodal models, training graduate researchers across these areas. - Departments: Computer Science - Research topics: Computer Vision, ML Theory, NLP/LLMs - Email: saenko@bu.edu - Website: https://ai.bu.edu/ - Last verified: 2026-08-22 ### Venkatesh Saligrama https://terrierintelligence.com/professors/venkatesh-saligrama A machine learning researcher who studies how models can train and predict under practical constraints such as limited computation, sparse labels, and distributed devices. His methods span federated learning, zero-shot and few-shot recognition, and bias mitigation, and he advises doctoral students working on these problems. - Departments: Electrical & Computer Engineering, Systems Engineering - Research topics: ML Theory, Computer Vision, Statistics - Email: srv@bu.edu - Website: https://sites.bu.edu/data/ - Last verified: 2026-08-22 ### Brian Kulis https://terrierintelligence.com/professors/brian-kulis A machine learning researcher focused on large-scale optimization for problems such as metric learning, clustering, and content-based search, combining Bayesian methods with deep learning. His applications center on audio and visual data, and he teaches machine learning and deep learning courses while advising doctoral and undergraduate researchers. - Departments: ENG (ECE, SE), Computer Science, CDS - Research topics: ML Theory - Email: bkulis@bu.edu - Website: https://www.bu.edu/cs/profiles/brian-kulis/ - Last verified: 2026-08-22 ### Bryan Plummer https://terrierintelligence.com/professors/bryan-plummer A multimodal machine learning researcher who develops methods for combining vision and language, making neural networks efficient, and keeping models robust to label noise and domain shifts. His work spans explainable and fair AI, multimodal benchmarks, and self-supervised learning for medical imaging, with several completed doctoral advisees. - Departments: Computer Science - Research topics: Computer Vision, NLP/LLMs - Email: bplum@bu.edu - Website: https://www.bu.edu/cs/profiles/bplum/ - Last verified: 2026-08-22 ### Deepti Ghadiyaram https://terrierintelligence.com/professors/deepti-ghadiyaram A computer vision researcher who studies how to make vision and generative models safe, interpretable, and robust. Her group examines the inner workings of generative and multimodal large language models and applies them to problems including healthcare, while she teaches vision courses and mentors doctoral, master's, and undergraduate researchers. - Departments: Computer Science (affil. ECE, CDS) - Research topics: Computer Vision, Generative AI/Tools, AI Safety - Email: dghadiya@bu.edu - Website: https://deeptigp.github.io/ - Last verified: 2026-08-22 ### Boqing Gong https://terrierintelligence.com/professors/boqing-gong A computer vision researcher who studies visual recognition and video understanding, with attention to the safety, generalization, and efficiency of AI models. His methods include domain adaptation and transfer learning, long-tailed recognition, adversarial robustness, and self-supervised learning, grounded in the mathematical structure of each problem. - Departments: Computer Science - Research topics: Computer Vision, ML Theory - Email: bgong@bu.edu - Website: https://www.bu.edu/cs/profiles/boqing-gong/ - Last verified: 2026-08-22 ### Stan Sclaroff https://terrierintelligence.com/professors/stan-sclaroff A computer vision researcher whose work covers tracking, video-based analysis of human motion and gesture, and deformable shape matching and recognition. He founded BU's Image and Video Computing group and developed ImageRover, one of the first content-based image retrieval systems for the web. - Departments: Computer Science - Research topics: Computer Vision - Email: sclaroff@bu.edu - Website: https://www.bu.edu/cs/profiles/stan-sclaroff/ - Last verified: 2026-08-22 ### Derry Wijaya https://terrierintelligence.com/professors/derry-wijaya A natural language processing researcher who develops machine learning methods for machine translation, with emphasis on using well-annotated languages to improve translation of low-resource ones. Her work also examines verb semantics across languages and time and builds techniques for populating knowledge bases from text. - Departments: Computer Science - Research topics: NLP/LLMs, ML Theory - Email: wijaya@bu.edu - Website: https://www.bu.edu/cs/profiles/derry-wijaya/ - Last verified: 2026-08-22 ### Kayhan Batmanghelich https://terrierintelligence.com/professors/kayhan-batmanghelich A medical AI researcher who addresses explainability, data efficiency, multimodal fusion, and causality in machine learning for healthcare. His lab applies vision-language and diffusion models to problems such as lung disease and cancer imaging, and he teaches deep learning and machine learning courses while supervising graduate researchers. - Departments: Electrical & Computer Engineering - Research topics: Healthcare, ML Theory, Computer Vision - Email: batman@bu.edu - Website: https://www.batman-lab.com/ - Last verified: 2026-08-22 ### Simon Kasif https://terrierintelligence.com/professors/simon-kasif A computational biology researcher who connects AI and biomedical science in both directions, seeking methods that advance each field. His work applies machine learning, network biology, and algorithm design to gene function prediction, genomic systems biology, and studies of metabolic disease and aging, alongside questions of responsible AI use. - Departments: Biomedical Engineering / Bioinformatics, Computer Science - Research topics: Healthcare, ML Theory, Data Science - Email: kasif@bu.edu - Website: https://sites.bu.edu/phenogeno/ - Last verified: 2026-08-22 ### Dokyun Lee https://terrierintelligence.com/professors/dokyun-lee A business data scientist who combines text mining, machine learning, and causal inference to extract market and consumer insights from unstructured data. His research examines generative AI and algorithmic transparency in marketing and retail settings, and he teaches analytics courses and mentors doctoral students. - Departments: Questrom (Information Systems), CDS - Research topics: Data Science, NLP/LLMs, Generative AI/Tools - Email: dokyun@bu.edu - Website: https://www.leedokyun.com/ - Last verified: 2026-08-22 ### Emily Whiting https://terrierintelligence.com/professors/emily-whiting A computer graphics researcher who studies computational fabrication, examining how computation supports creative design of physical objects. Her group develops methods such as differentiable topology optimization and interlocking-structure design, drawing on engineering mechanics, and she teaches computational fabrication while advising doctoral researchers. - Departments: Computer Science - Research topics: HCI - Email: whiting@bu.edu - Website: https://shape.bu.edu/ - Last verified: 2026-08-22 ### Janusz Konrad https://terrierintelligence.com/professors/janusz-konrad A video and image processing researcher whose work spans computer vision, visual sensor networks, and 3D imaging. His lab develops multi-camera AI systems that estimate occupancy in large indoor spaces from overhead fisheye cameras, supporting applications in energy-efficient building management and emergency response. - Departments: Electrical & Computer Engineering - Research topics: Computer Vision - Email: jkonrad@bu.edu - Website: https://vip.bu.edu/ - Last verified: 2026-08-22 ### Prakash Ishwar https://terrierintelligence.com/professors/prakash-ishwar A statistical signal processing and machine learning researcher who develops model-based and data-driven tools for learning and inference problems. His work spans information theory, information-theoretic security, and visual information analysis, with applications that include people detection and activity recognition in video. - Departments: Electrical & Computer Engineering - Research topics: Computer Vision, ML Theory, Statistics - Email: pi@bu.edu - Website: https://vip.bu.edu/ - Last verified: 2026-08-22 ### Daniel Munro https://terrierintelligence.com/professors/daniel-munro A philosopher of mind and epistemologist whose work examines the nature and epistemic value of imagination, including storytelling and pretend play. He applies this theorizing to conspiracy thinking, religious cognition, and the behavior of artificial agents such as large language models. - Departments: Philosophy (CAS) - Research topics: Ethics, Policy - Email: dmunro@bu.edu - Last verified: 2026-08-22 ### Seth Villegas https://terrierintelligence.com/professors/seth-villegas A philosopher specializing in the ethics of emerging technology, with research on transhumanism, life-extension technologies, and AI companions designed to mimic deceased family members. He teaches responsible and ethical data science and AI in BU's online master's programs and hosts the DigEthix ethics podcast. - Departments: Philosophy (CAS) - Research topics: Ethics, Policy - Email: sethvill@bu.edu - Website: https://www.bu.edu/cds-faculty/profile/seth-villegas/ - Last verified: 2026-08-22 ### Naomi Caselli https://terrierintelligence.com/professors/naomi-caselli A cognitive scientist whose research examines how deaf children acquire American Sign Language and how early language deprivation affects vocabulary development. She builds resources such as the ASL-LEX lexicon database and directs BU's AI and Education Initiative and the Center on Sign Language and Deaf Education. - Departments: Wheelock College of Education & Human Development - Research topics: Education, NLP/LLMs - Email: nkc@bu.edu - Website: https://www.bu.edu/hic/profile/naomi-caselli/ - Last verified: 2026-08-22 ### Michael Chang https://terrierintelligence.com/professors/michael-chang A learning scientist and computer scientist who studies how AI can support teaching and learning beyond the dominant instructional practices of schooling. His work centers on the collaborative design of AI tools for education, and he serves as an assistant director of the Earl Center for Learning & Innovation. - Departments: Wheelock College of Education & Human Development - Research topics: Education - Email: machang@bu.edu - Website: https://www.bu.edu/cds-faculty/profile/michael-chang/ - Last verified: 2026-08-22 ### Elena Forzani https://terrierintelligence.com/professors/elena-forzani A literacy researcher who studies how elementary and secondary students read and evaluate online information, including judgments about credibility. She uses multiple and mixed methods to examine cognitive, metacognitive, and motivational dimensions of digital reading, informing the design of more equitable literacy instruction and assessment. - Departments: Wheelock College of Education & Human Development - Research topics: Education - Email: eforzani@bu.edu - Last verified: 2026-08-22 ### Jennifer Green https://terrierintelligence.com/professors/jennifer-green A child clinical psychologist whose research supports student mental health in schools, examining teacher identification of students with mental health needs, disparities in service access, and youth bullying. She develops survey measures of school bullying and evaluates prevention and mental health promotion programs in partnership with local districts. - Departments: Wheelock College of Education & Human Development - Research topics: Education - Email: jggreen@bu.edu - Website: https://www.bu.edu/hic/profile/jennifer-green/ - Last verified: 2026-08-22 ### Eshed Ohn-Bar https://terrierintelligence.com/professors/eshed-ohn-bar A computer vision and robotics researcher who develops machine learning for embodied, assistive, and autonomous systems. His lab builds perception, planning, and interaction systems for safety-critical settings such as autonomous driving and navigation assistance for blind and visually impaired pedestrians, tested with community partners. - Departments: Electrical & Computer Engineering - Research topics: Computer Vision, Robotics - Email: eohnbar@bu.edu - Website: https://www.bu.edu/hic/profile/eshed-ohn-bar/ - Last verified: 2026-08-22 ### Ola Ozernov-Palchik https://terrierintelligence.com/professors/ola-ozernov-palchik A cognitive neuroscientist who examines the brain and cognitive mechanisms of language and literacy development, with a focus on reading comprehension and dyslexia. She applies tools from neuroimaging and machine learning to predict reading difficulties and to build evidence-based, personalized approaches to early literacy assessment and intervention. - Departments: Wheelock College of Education & Human Development, Hariri Institute - Research topics: Education, Healthcare - Email: oozernov@bu.edu - Website: https://www.bu.edu/hic/profile/ola-ozernov-palchik/ - Last verified: 2026-08-22 ### Charalampos (Babis) Tsourakakis https://terrierintelligence.com/professors/charalampos-tsourakakis An algorithms researcher whose work spans large-scale graph mining and machine learning, including methods for finding dense subgraphs in massive networks. His research applies these techniques to problems such as anomaly detection, community detection, and web graph analysis, and he has built graph mining libraries adopted in industry. - Departments: Computer Science - Research topics: Data Science, ML Theory - Email: ctsourak@bu.edu - Website: https://tsourakakis.com/ - Last verified: 2026-08-22 ### Mark Bun https://terrierintelligence.com/professors/mark-bun A theoretical computer scientist who studies algorithmic data privacy, applying complexity theory to questions about differential privacy and its connections to machine learning. His work examines the computational complexity of private learning, relationships between privacy and online prediction, and polynomial approximations to Boolean functions. - Departments: Computer Science - Research topics: AI Safety, ML Theory, Ethics - Email: mbun@bu.edu - Website: https://cs-people.bu.edu/mbun/ - Last verified: 2026-08-22 ### Kevin Gold https://terrierintelligence.com/professors/kevin-gold A computer scientist and educator who teaches introductory data science, machine learning, and AI, and studies how large language models can support learning without short-circuiting it. His background spans industry and research roles at Google, MIT Lincoln Laboratory, and Epson, along with interests in modeling human behavior. - Departments: Computing & Data Sciences - Research topics: ML Theory, Education - Email: klgold@bu.edu - Website: https://www.bu.edu/cds-faculty/profile/klgold/ - Last verified: 2026-08-22 ### Roberto Tron https://terrierintelligence.com/professors/roberto-tron A robotics researcher whose work combines control theory, computer vision, and machine learning for teams of robotic agents and human-robot interaction. He studies safety and performance of multi-robot systems using tools from Riemannian geometry and optimization, and develops distributed sensing platforms that model human motion to support aging in place. - Departments: Mechanical Engineering - Research topics: Robotics - Email: tron@bu.edu - Website: https://www.bu.edu/eng/profile/roberto-tron/ - Last verified: 2026-08-22 ### Adam Smith https://terrierintelligence.com/professors/adam-smith A theoretical computer scientist working on data privacy and cryptography and their connections to machine learning, statistics, and information theory. He co-invented differential privacy, a rigorous framework for analyzing privacy in statistical databases, work recognized with the 2017 Gödel Prize and now used in deployed systems. - Departments: Computer Science, College of Arts and Sciences - Research topics: ML Theory, Data Science, Social Science, Security - Email: ads22@bu.edu - Website: https://www.bu.edu/cs/profiles/adam-smith/ - Last verified: 2026-08-22 ### Ajay Joshi https://terrierintelligence.com/professors/ajay-joshi A computer engineering researcher who designs energy-efficient computing systems, spanning computer architecture, hardware security, and silicon photonics. His group develops heterogeneously integrated electronic-photonic accelerators intended to run AI workloads faster and more efficiently, work supported by a National Science Foundation award. - Departments: Electrical and Computer Engineering, College of Engineering - Research topics: ML Theory, Robotics, Neuroscience, Security - Email: joshi@bu.edu - Website: https://www.bu.edu/eng/profile/ajay-joshi/ - Last verified: 2026-08-22 ### Alan Marscher https://terrierintelligence.com/professors/alan-marscher An astrophysicist who studies blazars, active galactic nuclei that launch plasma jets moving near light speed. With collaborators and students in BU's blazar research group, he builds physical models of jet formation and particle acceleration and interprets multifrequency monitoring observations from radio through gamma-ray telescopes. - Departments: Astronomy, College of Arts and Sciences - Research topics: ML Theory, Data Science, Physical Sciences - Email: marscher@bu.edu - Website: https://www.bu.edu/hic/profile/alan-marscher/ - Last verified: 2026-08-22 ### Alexander Olshevsky https://terrierintelligence.com/professors/alexander-olshevsky A control and optimization theorist whose work develops distributed algorithms that let networks of autonomous agents, such as vehicle formations and sensor networks, cooperate reliably. His recent research analyzes reinforcement learning methods, proving convergence guarantees and sample-complexity bounds for algorithms including temporal difference learning and actor-critic. - Departments: Electrical & Computer Engineering, College of Engineering - Research topics: ML Theory, Robotics, Healthcare, Data Science - Email: alexols@bu.edu - Website: https://www.bu.edu/eng/profile/alexander-olshevsky/ - Last verified: 2026-08-22 ### Alice Cronin-Golomb https://terrierintelligence.com/professors/alice-cronin-golomb A clinical neuropsychologist whose work examines how perception and cognition change in aging and neurodegenerative disease, with emphasis on the non-motor symptoms of Parkinson's disease. Her Vision and Cognition Laboratory combines visual psychophysics, neuropsychological assessment, portable brain imaging, and smartphone-based symptom tracking in these populations. - Departments: Psychological and Brain Sciences, College of Arts and Sciences - Research topics: ML Theory, Computer Vision, NLP/LLMs, Healthcare - Email: alicecg@bu.edu - Website: https://www.bu.edu/hic/profile/alice-cronin-golomb/ - Last verified: 2026-08-22 ### Alina Ene https://terrierintelligence.com/professors/alina-ene A theoretical computer scientist whose work designs and analyzes algorithms for combinatorial optimization, with emphasis on submodular functions and graphs. Her research examines the mathematical structure of these problems and applies the resulting algorithms to machine learning and the foundations of data science. - Departments: Computer Science, College of Arts and Sciences - Research topics: ML Theory, Data Science, Economy - Email: aene@bu.edu - Website: https://www.bu.edu/cs/profiles/aene/ - Last verified: 2026-08-22 ### Allyson Sgro https://terrierintelligence.com/professors/allyson-sgro A quantitative biologist whose work examines how cells communicate and coordinate collective behaviors such as tissue assembly, wound healing, and biofilm formation. Her laboratory combines optogenetics and microscopy with machine learning and mathematical modeling to build a predictive understanding of how multicellular systems organize themselves. - Departments: Biomedical Engineering, College of Engineering - Research topics: ML Theory, Healthcare, Neuroscience, Data Science - Email: asgro@bu.edu - Last verified: 2026-08-22 ### Alyssa Pierson https://terrierintelligence.com/professors/alyssa-pierson A robotics researcher whose work studies trust and cooperation in multi-agent systems, distributed robot control, and socially aware autonomy. She designs control algorithms that let teams of robots share tasks and interact safely with humans and each other in complex, dynamic environments. - Departments: Mechanical Engineering, College of Engineering - Research topics: Robotics - Email: pierson@bu.edu - Website: https://www.bu.edu/hic/profile/alyssa-pierson/ - Last verified: 2026-08-22 ### Anand Devaiah https://terrierintelligence.com/professors/anand-devaiah A skull base surgeon and health technology researcher whose work applies data analytics, AI, and ML to health care, including unlocking data held in siloed clinical repositories and developing digital biomarkers. He collaborates with startups and established companies to move new medical technologies into practice. - Departments: Otolaryngology, School of Medicine - Research topics: ML Theory, Healthcare, Neuroscience, Data Science - Email: adevaiah@bu.edu - Website: https://www.bu.edu/hic/profile/anand-devaiah/ - Last verified: 2026-08-22 ### Anatoly Temkin https://terrierintelligence.com/professors/anatoly-temkin A mathematician whose expertise centers on cryptography, with research interests in information security and curriculum design. He teaches undergraduate and graduate courses in discrete mathematics, cryptography, and algorithms, and received BU's Metcalf Award for Excellence in Teaching for his classroom work. - Departments: Computer Science, Metropolitan College - Research topics: ML Theory, Neuroscience, Data Science, Security - Email: temkin@bu.edu - Website: https://www.bu.edu/met/profile/anatoly-temkin/ - Last verified: 2026-08-22 ### Andrew Emili https://terrierintelligence.com/professors/andrew-emili A systems biologist whose work maps protein interaction networks, biochemical pathways, and macromolecular complexes on a large scale. His research develops proteomic, genomic, and bioinformatic technologies, using protein mass spectrometry and computational analysis to reveal how molecular associations function in health and disease. - Departments: Biochemistry (BUSM) and Biology (CAS), School of Medicine - Research topics: ML Theory, Healthcare, Data Science - Email: aemili@bu.edu - Website: https://www.bu.edu/hic/profile/andrew-emili/ - Last verified: 2026-08-22 ### Andrew Fitzpatrick https://terrierintelligence.com/professors/andrew-fitzpatrick A theoretical physicist whose work develops quantum field theory methods, with emphasis on effective field theories and scale-invariant systems. His current research uses the conformal bootstrap, which constrains theories through symmetry and consistency requirements, to study quantum gravity and dualities between seemingly different physical descriptions. - Departments: Physics, College of Arts and Sciences - Research topics: ML Theory, Physical Sciences - Email: fitzpatr@bu.edu - Website: https://www.bu.edu/hic/profile/andrew-fitzpatrick/ - Last verified: 2026-08-22 ### Andrew Lyasoff https://terrierintelligence.com/professors/andrew-lyasoff A mathematician whose work applies stochastic analysis to asset pricing and the study of continuous-time financial markets, including equilibrium in incomplete markets. His research develops computational methods for finance, such as spline cubatures for expectations of diffusion processes, and he wrote the MIT Press text Stochastic Methods in Asset Pricing. - Departments: Finance, School of Management - Research topics: ML Theory, Data Science, Physical Sciences, Economy - Email: alyasoff@bu.edu - Website: https://www.bu.edu/questrom/profiles/andrew-lyasoff/ - Last verified: 2026-08-22 ### Andrew Sabelhaus https://terrierintelligence.com/professors/andrew-sabelhaus A roboticist whose work builds control systems and AI for soft and flexible robots, combining computational intelligence with embodied intelligence. His Soft Robotics Control Lab develops algorithms for locomotion and manipulation that aim to make close physical contact between robots and humans verifiably safe. - Departments: Mechanical Engineering, College of Engineering - Research topics: ML Theory, Robotics, Healthcare, Data Science - Email: asabelha@bu.edu - Website: https://www.bu.edu/eng/profile/andrew-sabelhaus/ - Last verified: 2026-08-22 ### Andrew Sellars https://terrierintelligence.com/professors/andrew-sellars A technology lawyer whose scholarship examines how intellectual property and computer access laws apply to technology research and journalism. As founding director of BU's Technology Law Clinic, he has supervised law students representing student security researchers, journalists, and startups on privacy, cybersecurity, and media law questions. - Departments: Technology Law Clinic, School of Law - Research topics: ML Theory, Computer Vision, NLP/LLMs, Robotics - Email: sellars@bu.edu - Last verified: 2026-08-22 ### Anthony Rosellini https://terrierintelligence.com/professors/anthony-rosellini A clinical psychologist whose work studies the onset and course of anxiety and mood disorders. His research applies machine learning to clinical and epidemiologic data to build prediction tools that identify people at risk for these conditions, with applications including depression and suicide risk in military populations. - Departments: Psychological and Brain Sciences, College of Arts and Sciences - Research topics: ML Theory, Healthcare, Neuroscience, Data Science - Email: ajrosell@bu.edu - Website: https://www.bu.edu/hic/profile/anthony-rosellini/ - Last verified: 2026-08-22 ### Archana Venkataraman https://terrierintelligence.com/professors/archana-venkataraman A biomedical imaging and AI researcher whose work connects machine learning with clinical neuroscience. Her Neural Systems Analysis Laboratory develops algorithms for multimodal brain imaging data, including methods that localize seizure onset in epilepsy and models that characterize disorders such as autism and schizophrenia. - Departments: Electrical and Computer Engineering, College of Engineering - Research topics: ML Theory, NLP/LLMs, Healthcare, Neuroscience - Email: archanav@bu.edu - Website: https://www.bu.edu/eng/profile/archana-venkataraman-ph-d/ - Last verified: 2026-08-22 ### Ari Trachtenberg https://terrierintelligence.com/professors/ari-trachtenberg An algorithms and security researcher whose work develops methods for data synchronization across distributed systems, error-correcting codes, and cybersecurity for smartphones and networked devices. His synchronization research includes protocols that reconcile transaction pools in large-scale blockchain networks, and he directs BU's Red Hat Collaboratory. - Departments: Electrical and Computer Engineering, College of Engineering - Research topics: ML Theory, Robotics, Data Science, Security - Email: trachten@bu.edu - Website: https://www.bu.edu/eng/profile/ari-trachtenberg/ - Last verified: 2026-08-22 ### Ashok Cutkosky https://terrierintelligence.com/professors/ashok-cutkosky A machine learning theorist who designs optimization algorithms for training models, focusing on online learning, stochastic non-convex optimization, and parameter-free methods that remove manual hyperparameter tuning. He teaches BU courses on machine learning and optimization and advises PhD and undergraduate researchers. - Departments: Electrical and Computer Engineering, College of Engineering - Research topics: ML Theory, Healthcare, Neuroscience, Data Science - Email: cutkosky@bu.edu - Website: https://www.bu.edu/eng/profile/ashok-cutkosky/ - Last verified: 2026-08-22 ### Ayse Coskun https://terrierintelligence.com/professors/ayse-coskun A computer systems researcher whose work spans design automation, large-scale computer systems, and applied machine learning, with a focus on energy efficiency. She develops modeling and optimization methods that manage performance and power in data centers and high-performance computing clusters. - Departments: Electrical and Computer Engineering, College of Engineering - Research topics: ML Theory, Robotics, Physical Sciences, Environment - Email: acoskun@bu.edu - Website: https://www.bu.edu/hic/profile/ayse-coskun/ - Last verified: 2026-08-22 ### Ayse Lokmanoglu https://terrierintelligence.com/professors/ayse-lokmanoglu A computational social scientist who examines how supremacist ideologies, disinformation, and conspiracy theories spread online through state and non-state actors. She applies automated text and visual analysis, topic modeling, and network analysis to large-scale social media data, with attention to race, gender, and religion. - Departments: Emerging Media Studies, College of Communication - Research topics: Social Science - Email: alokman@bu.edu - Website: https://www.bu.edu/com/profile/ayse-lokmanoglu/ - Last verified: 2026-08-22 ### Azer Bestavros https://terrierintelligence.com/professors/azer-bestavros A computer scientist specializing in distributed systems and trustworthy computing, with contributions to internet content delivery, cloud resource management, and privacy-preserving data analytics. He served as founding director of BU's Hariri Institute and now leads the Faculty of Computing & Data Sciences as associate provost. - Departments: Computer Science, College of Arts and Sciences - Research topics: ML Theory, Computer Vision, NLP/LLMs, Robotics - Email: best@bu.edu - Website: https://www.bu.edu/cs/profiles/best/ - Last verified: 2026-08-22 ### Belinda Borrelli https://terrierintelligence.com/professors/belinda-borrelli A clinical psychologist who develops and tests digital health interventions that motivate behavior change, particularly among people not yet motivated to change. Her work uses mobile platforms such as apps, text messaging, and virtual reality for smoking cessation, oral health, and adherence to chronic disease treatment. - Departments: Center for Behavioral Science Research, Goldman School of Dental Medicine - Research topics: ML Theory, Computer Vision, NLP/LLMs, Robotics - Email: belindab@bu.edu - Website: https://www.bu.edu/hic/profile/belinda-borrelli/ - Last verified: 2026-08-22 ### Benjamin Lubin https://terrierintelligence.com/professors/benjamin-lubin A researcher at the intersection of computer science, game theory, and economics who designs market mechanisms such as combinatorial auctions and exchanges. He also applies spectral graph theory, network science, and machine learning to analyze social networks and improve healthcare delivery, and directs a master's program in digital technology. - Departments: Information systems, Questrom School of Business - Research topics: ML Theory, Data Science, Economy - Email: blubin@bu.edu - Website: https://www.bu.edu/questrom/profiles/benjamin-lubin/ - Last verified: 2026-08-22 ### Bin Gu https://terrierintelligence.com/professors/bin-gu An information systems researcher who examines how information technologies and AI can address information asymmetry and social inequity in business and society. His studies trace these dynamics across settings such as fintech, digital platforms, and online social media, connecting technology design to economic and social outcomes. - Departments: Information Systems, Questrom School of Business - Research topics: ML Theory, Computer Vision, NLP/LLMs, Robotics - Email: bgu@bu.edu - Website: https://www.bu.edu/questrom/profiles/bin-gu/ - Last verified: 2026-08-22 ### Bindu Kalesan https://terrierintelligence.com/professors/bindu-kalesan A clinical epidemiologist and biostatistician who studies the public health consequences of firearm violence, including injury survivorship, and long-term outcomes after cardiovascular disease and traumatic injury. Her methods include longitudinal cohort studies, meta-analysis, and spatiotemporal modeling of large clinical and population datasets. - Departments: Medicine, School of Medicine - Research topics: ML Theory, Healthcare, Data Science, Statistics - Email: kalesan@bu.edu - Website: https://www.bu.edu/hic/profile/bindu-kalesan/ - Last verified: 2026-08-22 ### Björn Reinhard https://terrierintelligence.com/professors/bjorn-reinhard A nanomaterials chemist who develops plasmonic probes and functional optical materials for imaging, sensing, and photonics. His interdisciplinary group studies the interface between nanotechnology and biological systems, using engineered nanostructures to probe and control cellular processes, characterize nanoparticle-cell interactions, and profile tumor cells. - Departments: Chemistry, College of Arts and Sciences - Research topics: ML Theory, Physical Sciences - Email: bmr@bu.edu - Website: https://www.bu.edu/eng/profile/bjorn-reinhard/ - Last verified: 2026-08-22 ### Brian Cleary https://terrierintelligence.com/professors/brian-cleary A computational biologist who applies compressed sensing and related algorithmic techniques to make genomic experiments more efficient. His group develops computational and laboratory methods for composite imaging transcriptomics, compressed genetic perturbation screens, and viral infection assays, recovering rich biological signal from far fewer measurements. - Departments: Biomedical Engineering, Biology - Research topics: ML Theory, Healthcare - Email: bcleary@bu.edu - Website: https://www.bu.edu/cds-faculty/profile/bcleary/ - Last verified: 2026-08-22 ### Brian DePasquale https://terrierintelligence.com/professors/brian-depasquale A computational neuroscientist whose research sits at the boundary of machine learning and theoretical neuroscience, developing models of how biological neural circuits give rise to computation and behavior. He teaches a foundations course on biomedical data analysis and machine learning. - Departments: Biomedical Engineering, College of Engineering - Research topics: ML Theory, Neuroscience, Data Science - Email: bddepasq@bu.edu - Website: https://www.bu.edu/eng/profile/brian-depasquale-ph-d/ - Last verified: 2026-08-22 ### Carol Neidle https://terrierintelligence.com/professors/carol-neidle A linguist specializing in American Sign Language (ASL) who collaborates with computer scientists on video-based sign language recognition. Her work has produced computational tools such as SignStream and large annotated ASL video corpora that support both linguistic analysis and computer vision research. - Departments: Linguistics, College of Arts and Sciences - Research topics: ML Theory, Computer Vision, NLP/LLMs, HCI - Email: carol@bu.edu - Website: https://www.bu.edu/linguistics/profile/carol-neidle/ - Last verified: 2026-08-22 ### Catherine Caldwell-Harris https://terrierintelligence.com/professors/catherine-caldwell-harris A psycholinguist who studies how bilingual speakers process language and emotion, combining experimental measures such as skin conductance with cross-cultural surveys. Her current work also examines large language models from a psychological perspective, with undergraduate researchers participating through BU's Undergraduate Research Opportunities Program. - Departments: Psychological and Brain Sciences, College of Arts and Sciences - Research topics: ML Theory, Computer Vision, NLP/LLMs, Robotics - Email: charris@bu.edu - Website: https://www.bu.edu/hic/profile/catherine-caldwell-harris/ - Last verified: 2026-08-22 ### Catherine Espaillat https://terrierintelligence.com/professors/catherine-espaillat An astrophysicist who studies planet formation, searching protoplanetary disks around young stars for the footprints that forming planets leave behind. She combines multiwavelength observations from X-ray to radio with computer simulations and radiative transfer modeling, and co-leads an international consortium analyzing Hubble Space Telescope data. - Departments: Astronomy, College of Arts and Sciences - Research topics: ML Theory, Physical Sciences - Email: cce@bu.edu - Website: https://www.bu.edu/hic/profile/catherine-espaillat/ - Last verified: 2026-08-22 ### Cathie Jo Martin https://terrierintelligence.com/professors/cathie-jo-martin A comparative political scientist who applies computational text analysis to centuries of British and Danish literature to trace the cultural origins of national education systems. Her work examines how these systems shape social inclusion and outcomes for low-skill youth, pairing literary corpora with political-economy scholarship. - Departments: Political Science, College of Arts and Sciences - Research topics: ML Theory, Data Science, Social Science, Humanities - Email: cjmartin@bu.edu - Last verified: 2026-08-22 ### Chao Zhang https://terrierintelligence.com/professors/chao-zhang A computational biologist who develops machine learning and statistical methods for next-generation sequencing data, including single-cell RNA sequencing. His research builds deep learning frameworks to uncover temporal changes in host-microbiome interactions and applies genomic analysis to stem cell biology, cancer, and neurodegenerative disease. - Departments: Medicine, School of Medicine - Research topics: ML Theory, Healthcare, Neuroscience, Physical Sciences - Email: chz2009@bu.edu - Website: https://www.bu.edu/hic/profile/chao-zhang/ - Last verified: 2026-08-22 ### Charlene Ong https://terrierintelligence.com/professors/charlene-ong A neurointensivist who develops and validates machine learning and dynamic risk-prediction tools to guide treatment decisions for patients with severe brain injury, including ischemic and hemorrhagic stroke. Her research draws on physiologic biomarkers and multimodal clinical data to improve outcomes in neurocritical care. - Departments: Medicine, Chobanian and Avedisian School of Medicine - Research topics: ML Theory, Neuroscience - Email: cjong@bu.edu - Website: https://www.bu.edu/hic/profile/charlene-ong/ - Last verified: 2026-08-22 ### Chris McVey https://terrierintelligence.com/professors/chris-mcvey A writing studies scholar and teacher whose work examines AI literacy, ethics, and student practices with generative AI. He teaches courses on AI and writing, studies student beliefs about generative AI tools, and participates in national curriculum initiatives on AI in higher education. - Departments: Writing Program - Research topics: Generative AI/Tools, Humanities, Education - Email: cmcvey@bu.edu - Website: https://www.bu.edu/writingprogram/profile/christopher-mcvey/ - Last verified: 2026-08-22 ### Christoph Nolte https://terrierintelligence.com/professors/christoph-nolte A conservation scientist who combines remote sensing, property and sales data, causal inference, and predictive machine learning to measure the effects and costs of land conservation. His projects estimate what protection actually costs, evaluate biodiversity and climate policies, and value environmental amenities and risks. - Departments: Earth & Environment, College of Arts and Sciences - Research topics: ML Theory, Data Science, Environment, Social Science - Email: chrnolte@bu.edu - Website: https://www.bu.edu/earth/profiles/christoph-nolte/ - Last verified: 2026-08-22 ### Christos Cassandras https://terrierintelligence.com/professors/christos-cassandras A control and systems theorist who studies discrete-event and hybrid systems, cooperative multi-agent control, and optimization for cyber-physical systems. His work applies these methods to smart cities and connected automated vehicles, including adaptive traffic-light control, smart parking, and safe coordination of autonomous vehicle networks. - Departments: Division of Systems Engineering/ECE, College of Engineering - Research topics: ML Theory, Robotics, Healthcare, Physical Sciences - Email: cgc@bu.edu - Website: https://www.bu.edu/eng/profile/christos-cassandras/ - Last verified: 2026-08-22 ### Chuanfei Dong https://terrierintelligence.com/professors/chuanfei-dong A computational plasma physicist who models interactions between stars and terrestrial planets in the solar system and beyond, along with magnetic reconnection, turbulence, and wave-particle interaction. His research combines high-performance simulation with physics-informed machine learning to study space plasmas and laser-plasma interaction. - Departments: Department of Astronomy, College of Arts and Sciences - Research topics: ML Theory, Data Science, Physical Sciences, Environment - Email: dcfy@bu.edu - Website: https://www.bu.edu/eng/profile/chuanfei-dong-phd/ - Last verified: 2026-08-22 ### Clem Karl https://terrierintelligence.com/professors/clem-karl A computational imaging researcher who develops statistical methods for signal and image processing, estimation, and image reconstruction. His work extracts information from noisy, uncertain data in applications spanning medical tomography and magnetic resonance imaging, synthetic aperture radar target recognition, and geophysical and atmospheric sensing. - Departments: Electrical & Computer Engineering, College of Engineering - Research topics: ML Theory, Healthcare, Data Science - Email: wckarl@bu.edu - Website: https://www.bu.edu/hic/profile/clem-karl/ - Last verified: 2026-08-22 ### Conor Mack https://terrierintelligence.com/professors/conor-mack A strategy and innovation educator whose interests center on machine learning, large-scale data mining, and knowledge discovery in business applications such as business intelligence and e-commerce. Alongside teaching, he directs a venture studio and accelerator for early-stage companies building AI and Web3 technologies. - Departments: Strategy & Innovation, Questrom School of Business - Research topics: ML Theory, Robotics, Data Science, Social Science - Email: cjm23@bu.edu - Website: https://www.bu.edu/questrom/profiles/conor-mack/ - Last verified: 2026-08-22 ### Dan Li https://terrierintelligence.com/professors/dan-li An urban climate scientist who uses weather and climate models, fluid mechanics, and observational data to study how urbanization and climate change reshape city heat, water, and energy cycles. His research examines urban heat islands and heat waves to inform planning for hotter cities. - Departments: Earth and Environment, College of Arts and Sciences - Research topics: ML Theory, Physical Sciences, Environment - Email: lidan@bu.edu - Website: https://www.bu.edu/earth/profiles/dan-li/ - Last verified: 2026-08-22 ### Daniel Fulford https://terrierintelligence.com/professors/daniel-fulford A psychologist who studies motivation and social processes in psychopathology, using smartphone-based experience sampling and behavioral sensing to capture daily life. His research develops mobile interventions, including an app that combines social skills training with motivation support to improve social functioning in schizophrenia. - Departments: Occupational Therapy and Psychological & Brain Sciences, Sargent College - Research topics: ML Theory, Healthcare, Neuroscience, Security - Email: dfulford@bu.edu - Website: https://www.bu.edu/hic/profile/daniel-fulford/ - Last verified: 2026-08-22 ### Daniel Segrè https://terrierintelligence.com/professors/daniel-segre A computational biologist who studies the structure, dynamics, and origin of metabolism from single cells to microbial ecosystems. His group combines mathematical models with metagenomic sequencing to predict metabolism-mediated microbial interactions, developing simulation frameworks with applications in human microbiome research, biogeochemical cycling, and synthetic ecology. - Departments: Biology, College of Arts and Sciences - Research topics: ML Theory, Healthcare, Physical Sciences, Environment - Email: dsegre@bu.edu - Website: https://www.bu.edu/cds-faculty/profile/dsegre/ - Last verified: 2026-08-22 ### Daniel Sussman https://terrierintelligence.com/professors/daniel-sussman A statistician who develops methods for network data, including node embeddings, graph matching, and causal inference under interference. His work examines trade-offs between computational constraints and statistical efficiency and applies network inference to brain connectomes, molecular and social networks, and knowledge graphs. - Departments: Mathematics and Statistics, College of Arts and Sciences - Research topics: ML Theory, Healthcare, Neuroscience, Data Science - Email: sussman@bu.edu - Last verified: 2026-08-22 ### David Campbell https://terrierintelligence.com/professors/david-campbell A theoretical physicist who studies nonlinear phenomena and complex systems, including intrinsic localized modes, novel electronic materials, and electron transport in semiconductor superlattices. His work uses analytical theory and computational simulation to explain how nonintegrable dynamical systems approach equilibrium or remain trapped in metastable states. - Departments: Physics, College of Arts and Sciences - Research topics: ML Theory, Physical Sciences - Email: dkcampbe@bu.edu - Website: https://www.bu.edu/eng/profile/david-campbell/ - Last verified: 2026-08-22 ### Deepak Kumar https://terrierintelligence.com/professors/deepak-kumar A clinician-scientist who develops technology-enabled movement interventions for adults with knee osteoarthritis, aiming for sustained improvements in pain and physical function. His research tests AI-powered wearable sensors that assess patients' movement patterns at home and in the clinic, supporting more accessible rehabilitation care. - Departments: Physical Therapy & Athletic Training, Sargent College - Research topics: ML Theory, Healthcare, Data Science, Statistics - Email: kumard@bu.edu - Website: https://www.bu.edu/hic/profile/deepak-kumar/ - Last verified: 2026-08-22 ### Diane Joseph-McCarthy https://terrierintelligence.com/professors/diane-joseph-mccarthy A computational chemist whose work applies molecular modeling, structure-based design, and machine learning to early-stage drug discovery. Her research develops fragment-based lead discovery methods and combines cryo-electron microscopy structural data with AI to identify and optimize candidate therapeutics, including antibacterials. - Departments: Biomedical Engineering, College of Engineering - Research topics: ML Theory, Healthcare, Physical Sciences - Email: djosephm@bu.edu - Website: https://www.bu.edu/eng/profile/diane-joseph-mccarthy/ - Last verified: 2026-08-22 ### Douglas Densmore https://terrierintelligence.com/professors/douglas-densmore A computer engineer whose research builds design-automation tools for synthetic biology, adapting techniques from electronic design automation to living systems. His group develops programming languages, software tools, and microfluidic platforms for designing, assembling, and testing engineered biological circuits with predictable behavior. - Departments: Electrical and Computer Engineering, College of Engineering - Research topics: ML Theory, Healthcare - Email: dougd@bu.edu - Website: https://www.bu.edu/eng/profile/douglas-densmore/ - Last verified: 2026-08-22 ### Dylan Walker https://terrierintelligence.com/professors/dylan-walker A computational social scientist whose work measures how information, behaviors, and products spread through online social networks. He combines randomized experiments on large platforms with causal analysis of observational data to study peer influence, misinformation, and how platform design shapes collective outcomes. - Departments: Information Systems, Questrom School of Business - Research topics: ML Theory, Data Science, Social Science, Policy - Email: dtwalker@bu.edu - Website: https://www.bu.edu/hic/profile/dylan-walker/ - Last verified: 2026-08-22 ### Elaine Nsoesie https://terrierintelligence.com/professors/elaine-nsoesie A computational epidemiologist whose research applies data science and machine learning to public health surveillance. She studies how data from social media, search engines, and mobile phones can track disease and inform policy, and how these tools can advance health equity. - Departments: Global Health, School of Public Health - Research topics: ML Theory, Healthcare, Statistics - Email: onelaine@bu.edu - Website: https://www.bu.edu/cds-faculty/profile/elaine-nsoesie/ - Last verified: 2026-08-22 ### Elizabeth Barnes https://terrierintelligence.com/professors/elizabeth-barnes A climate scientist whose research develops explainable AI methods to study how the Earth system varies, becomes predictable, and changes over time. Her group designs deep-learning tools that mirror scientific reasoning, applying them to questions about climate variability, prediction, and human-Earth system futures. - Departments: Earth & Environment, Computing & Data Sciences, College of Arts & Sciences, CDS - Research topics: Environment - Email: eabarnes@bu.edu - Website: https://www.bu.edu/earth/profiles/elizabeth-barnes/ - Last verified: 2026-08-22 ### Emily Ryan https://terrierintelligence.com/professors/emily-ryan A computational engineer whose research models reactive transport, fluid mechanics, and electrochemistry in energy systems. Her Computational Energy Laboratory develops multiphysics simulations to study advanced batteries, fuel cells, and carbon capture, including work on understanding and suppressing dendrite growth that limits battery life. - Departments: Mechanical Engineering, College of Engineering - Research topics: ML Theory, Physical Sciences - Email: ryanem@bu.edu - Website: https://www.bu.edu/eng/profile/emily-ryan-ph-d/ - Last verified: 2026-08-22 ### Emma Lejeune https://terrierintelligence.com/professors/emma-lejeune A computational mechanics researcher whose work integrates machine learning with physics-based simulation to characterize and predict the mechanical behavior of heterogeneous materials and biological systems. Her group builds benchmark datasets and metamodels that let researchers evaluate ML approaches to problems such as brittle fracture. - Departments: Mechanical Engineering, College of Engineering - Research topics: ML Theory, Healthcare, Data Science, Physical Sciences - Email: elejeune@bu.edu - Website: https://www.bu.edu/eng/profile/emma-lejeune/ - Last verified: 2026-08-22 ### Emma Wiles https://terrierintelligence.com/professors/emma-wiles An economist whose research examines how AI reshapes labor markets, focusing on search, matching, and hiring. She runs randomized experiments in the lab and field and analyzes large-scale platform data to study questions such as algorithmic writing assistance for job seekers and generative AI's effects on knowledge workers. - Departments: Information Systems, Questrom School of Business - Research topics: HCI - Email: ewiles@bu.edu - Website: https://www.bu.edu/questrom/profiles/emma-wiles/ - Last verified: 2026-08-22 ### Erol Pekoz https://terrierintelligence.com/professors/erol-pekoz An applied probabilist whose research develops approximation methods for probability distributions and models of networks, queueing, and reliability. He applies these tools to operations management and healthcare, including statistical methods for measuring care quality and comparing performance across healthcare providers. - Departments: Operations & Technology Management, Questrom School of Business - Research topics: ML Theory, Healthcare, Data Science, Statistics - Email: pekoz@bu.edu - Website: https://www.bu.edu/eng/profile/erol-pekoz/ - Last verified: 2026-08-22 ### Eugene Pinsky https://terrierintelligence.com/professors/eugene-pinsky A computer scientist whose research designs computationally simple, explainable machine learning methods for prediction and classification. His published work spans financial modeling, time-series analysis, and clustering, and he has developed core data science courses and led student projects in applied machine learning. - Departments: Computer Science, Metropolitan College - Research topics: ML Theory, Healthcare, Neuroscience, Data Science - Email: epinsky@bu.edu - Website: https://www.bu.edu/met/profile/eugene-pinsky/ - Last verified: 2026-08-22 ### Evimaria Terzi https://terrierintelligence.com/professors/evimaria-terzi A computer scientist whose research develops algorithms for data mining and machine learning, with emphasis on social network analysis, recommendation systems, and clustering. Her recent work extends these algorithmic methods to problems in online learning, urban informatics, and large language models. - Departments: Computer Science, College of Arts and Sciences - Research topics: ML Theory, Data Science, Environment - Email: evimaria@bu.edu - Website: https://www.bu.edu/cs/profiles/evimaria-terzi/ - Last verified: 2026-08-22 ### Gabriel Ocker https://terrierintelligence.com/professors/gabriel-ocker A theoretical neuroscientist whose research studies how the structure of neuronal networks shapes their activity and function. His group builds mathematical models of neural circuits using dynamical systems, stochastic processes, and statistical physics, and tests model predictions against neural data from experimental collaborators. - Departments: Mathematics and Statistics, College of Arts and Sciences - Research topics: ML Theory, Neuroscience, Physical Sciences - Email: gkocker@bu.edu - Last verified: 2026-08-22 ### Gareth Morgan https://terrierintelligence.com/professors/gareth-morgan A protein biochemist whose research examines why antibody light chains misfold and aggregate into amyloid fibrils in light-chain (AL) amyloidosis. His group combines biochemical experiments with computational structure prediction to understand light-chain instability and to develop small molecules that stabilize the proteins as potential therapies. - Departments: Amyloidosis Center and Department of Medicine, School of Medicine - Research topics: ML Theory, Healthcare, Physical Sciences - Email: gjmorgan@bu.edu - Website: https://www.bu.edu/hic/profile/gareth-morgan/ - Last verified: 2026-08-22 ### Georgios Zervas https://terrierintelligence.com/professors/georgios-zervas A quantitative marketing researcher whose work sits at the intersection of data science and economics, using large-scale data to study online platforms and marketplaces. His research examines the sharing economy's impact on incumbent industries, online reputation and reviews, and how digital markets shape competition. - Departments: Marketing, Questrom School of Business - Research topics: ML Theory, Data Science - Email: zg@bu.edu - Website: https://www.bu.edu/questrom/profiles/georgios-zervas/ - Last verified: 2026-08-22 ### Gerdus Benade https://terrierintelligence.com/professors/gerdus-benade An operations researcher working at the intersection of computer science and economics, studying group decision-making under uncertainty and the fair division of resources. His work applies optimization and computational social choice to civic processes such as voting, participatory budgeting, and political districting. - Departments: Information Systems, Questrom School of Business - Research topics: ML Theory, Data Science, Social Science, Policy - Email: benade@bu.edu - Website: https://www.bu.edu/questrom/profiles/gerdus-benade/ - Last verified: 2026-08-22 ### Gerry Tsoukalas https://terrierintelligence.com/professors/gerry-tsoukalas A business technology researcher who examines how emerging technologies change the way firms operate, finance themselves, and design platforms. His work covers blockchain governance, token economics, and fintech platform design, with recent projects on AI in business and human-AI collaboration. - Departments: Information Systems, Questrom School of Business - Research topics: ML Theory, Data Science, Social Science, Economy - Email: gerryt@bu.edu - Website: https://www.bu.edu/questrom/profiles/gerry-tsoukalas/ - Last verified: 2026-08-22 ### Gianluca Stringhini https://terrierintelligence.com/professors/gianluca-stringhini A security researcher who applies data-driven methods to understand and mitigate malicious activity online. By collecting and analyzing large-scale datasets with machine learning, statistical analysis, and systems design, he studies threats such as malware, coordinated harassment, and influence operations, and builds techniques to counter them. - Departments: Electrical and Computer Engineering, College of Engineering - Research topics: ML Theory, Social Science, Security, Ethics - Email: gian@bu.edu - Website: https://www.bu.edu/eng/profile/gianluca-stringhini-ph-d/ - Last verified: 2026-08-22 ### Gustavo Schwenkler https://terrierintelligence.com/professors/gustavo-schwenkler A financial economist who develops statistical and computational tools for measuring financial risk, spanning asset pricing, credit and systemic risk, and cryptocurrencies. His econometric work includes machine learning methods that extract networks of economically linked firms from news text to study how risk spreads. - Departments: Finance, Questrom School of Business - Research topics: ML Theory, Data Science, Physical Sciences, Social Science - Email: gas@bu.edu - Last verified: 2026-08-22 ### Hadi Nia https://terrierintelligence.com/professors/hadi-nia A mechanobiology researcher who develops tools and models at the interface of physical sciences, biology, and immunology to study cancer and lung disease. His group examines mechanical forces in the tumor microenvironment and combines biophysical modeling with AI to detect lung cancer from computed tomography scans. - Departments: Biomedical Engineering, College of Engineering - Research topics: ML Theory, Healthcare, Data Science, Statistics - Email: htnia@bu.edu - Website: https://www.bu.edu/eng/profile/hadi-nia-ph-d/ - Last verified: 2026-08-22 ### Harold Park https://terrierintelligence.com/professors/harold-park A computational mechanics researcher who develops simulation techniques for material behavior from the atomic scale to the macroscale. His group studies topological mechanics, soft active materials, and phononic metamaterials, and integrates machine learning with atomistic simulation to search for materials with designed mechanical properties. - Departments: Mechanical Engineering, College of Engineering - Research topics: ML Theory, Physical Sciences - Email: parkhs@bu.edu - Website: https://www.bu.edu/eng/profile/harold-park-ph-d/ - Last verified: 2026-08-22 ### Helen Jenkins https://terrierintelligence.com/professors/helen-jenkins A biostatistician whose work applies statistical modeling to infectious disease data, with a focus on tuberculosis. She develops estimates of pediatric tuberculosis incidence and mortality and uses spatial methods to examine geographic variation in drug-resistant disease, aiming to inform public health policy and decision-making. - Departments: Biostatistics, School of Public Health - Research topics: ML Theory, Healthcare, Data Science, Statistics - Email: helenje@bu.edu - Website: https://www.bu.edu/hic/profile/helen-jenkins/ - Last verified: 2026-08-22 ### Hongwei Xi https://terrierintelligence.com/professors/hongwei-xi A programming languages researcher who applies advanced type theory to language design and implementation. He is the principal designer of ATS, a language that combines programming with theorem proving through dependent and linear types, supporting the construction of safe and reliable software systems. - Departments: Computer Science, College of Arts and Sciences - Research topics: Robotics, Economy - Email: hwxi@bu.edu - Website: https://www.bu.edu/cs/profiles/hongwei-xi/ - Last verified: 2026-08-22 ### Hua Wang https://terrierintelligence.com/professors/hua-wang A control systems researcher who studies nonlinear dynamics and the control of systems exhibiting complex behavior such as bifurcations. His research interests span nonlinear and intelligent control methods, including fuzzy control, with applications to robotics and to biomedical and energy systems. - Departments: Systems Engineering, College of Engineering - Research topics: Robotics - Email: wangh@bu.edu - Website: https://www.bu.edu/eng/profile/hua-wang/ - Last verified: 2026-08-22 ### Huimin Cheng https://terrierintelligence.com/professors/huimin-cheng A biostatistician who develops machine learning and AI methods grounded in statistical network analysis. Her research spans graph deep learning, causal inference, and network modeling techniques such as graphon-based methods, with applications to trustworthy large language models, knowledge graphs, and health data. - Departments: Biostatistics, School of Public Health - Research topics: Healthcare, Statistics - Email: HUIMIN23@BU.EDU - Website: https://www.bu.edu/hic/profile/huimin-cheng/ - Last verified: 2026-08-22 ### Ioannis Paschalidis https://terrierintelligence.com/professors/ioannis-paschalidis An optimization and control researcher who integrates stochastic modeling with machine learning to develop methods robust to noisy, incomplete data. His work applies these tools to computational medicine and biology, health analytics, and networked systems, and he directs the Hariri Institute, BU's computing research hub. - Departments: Electrical and Computer Engineering, College of Engineering - Research topics: ML Theory, Robotics, Healthcare, Neuroscience - Email: yannisp@bu.edu - Website: https://www.bu.edu/eng/profile/ioannis-paschalidis/ - Last verified: 2026-08-22 ### Irena Vodenska https://terrierintelligence.com/professors/irena-vodenska A finance researcher who applies network theory and complexity science to model interconnected financial systems, banking dynamics, and systemic risk propagation. Her work develops early warning indicators for financial crises and uses deep learning for natural language processing to mine news for factors affecting markets. - Departments: Administrative Sciences, Metropolitan College - Research topics: ML Theory, Economy - Email: vodenska@bu.edu - Website: https://www.bu.edu/met/profile/irena-vodenska/ - Last verified: 2026-08-22 ### Iván Fernández-Val https://terrierintelligence.com/professors/ivan-fernandez-val An econometrician whose research develops methods for nonlinear panel data models, quantile regression, and distributional and causal analysis, with applications in labor economics. His recent work examines how machine learning methods can be applied to causal inference questions in empirical economics. - Departments: Economics, College of Arts and Sciences - Research topics: ML Theory, Healthcare, Data Science, Statistics - Email: ivanf@bu.edu - Website: https://www.bu.edu/hic/profile/ivan-fernandez-val/ - Last verified: 2026-08-22 ### Jacob Bor https://terrierintelligence.com/professors/jacob-bor A population health researcher who applies the tools of economics and data science to study HIV treatment and prevention in southern Africa and structural drivers of health disparities in the United States. His methods work advances causal inference designs, including regression discontinuity, to estimate causal effects without randomized trials. - Departments: Global Health and Epidemiology, School of Public Health - Research topics: ML Theory, Healthcare, Statistics - Email: jbor@bu.edu - Website: https://www.bu.edu/hic/profile/jacob-bor/ - Last verified: 2026-08-22 ### James Chapman https://terrierintelligence.com/professors/james-chapman A materials informatics researcher who fuses physics-based simulation with machine learning to discover and design materials for energy generation and storage, corrosion resistance, and pollution mitigation. His group combines quantum-mechanical and multiscale modeling with learned models that rapidly predict properties of candidate materials under extreme conditions. - Departments: Mechanical Engineering, College of Engineering - Research topics: ML Theory, Data Science, Physical Sciences - Email: jc112358@bu.edu - Website: https://www.bu.edu/eng/profile/james-chapman/ - Last verified: 2026-08-22 ### James Feigenbaum https://terrierintelligence.com/professors/james-feigenbaum An economic historian and labor economist who studies inequality, intergenerational mobility, and health in the nineteenth- and twentieth-century United States. He develops machine learning methods for linking individuals across digitized historical census records, using the resulting data to trace the long-run effects of public policy and environmental shocks. - Departments: Economics, College of Arts and Sciences - Research topics: ML Theory, Data Science, Social Science, Economy - Email: jamesf@bu.edu - Website: https://www.bu.edu/hic/profile/james-feigenbaum/ - Last verified: 2026-08-22 ### James Katz https://terrierintelligence.com/professors/james-katz A communication researcher who examines how emerging media technologies, especially AI and mobile communication, change social interaction and everyday life. Through books and studies of technology adoption, he explores what these tools reveal about human nature and organizations, and he directs a project on AI's implications for communication. - Departments: Emerging Media Studies, College of Arts and Sciences - Research topics: ML Theory, Robotics, Healthcare, Data Science - Email: katz2020@bu.edu - Website: https://www.bu.edu/hic/profile/james-katz/ - Last verified: 2026-08-22 ### James McDaniel https://terrierintelligence.com/professors/james-mcdaniel A structural acoustics researcher who studies how vibrations and sound interact with complex structures and materials, from acoustic metamaterials to viscoelastic damping. He combines theory, computation, experiment, and machine learning to model dynamic systems, with applications in sound absorption, target identification, and the built environment. - Departments: Mechanical, College of Engineering - Research topics: ML Theory, Physical Sciences - Email: jgm@bu.edu - Website: https://www.bu.edu/hic/profile/james-mcdaniel/ - Last verified: 2026-08-22 ### Janet Freilich https://terrierintelligence.com/professors/janet-freilich A legal scholar who studies patent law and innovation policy through large-scale empirical analysis, including a dataset of over two million patents. Her work examines how untested prophetic examples, inaccurate information, and AI-derived drug discoveries shape what patents disclose and how the patent system handles scientific evidence. - Departments: Law, School of Law - Research topics: ML Theory, NLP/LLMs, Healthcare, Data Science - Email: janetf@bu.edu - Last verified: 2026-08-22 ### Jennifer Beane https://terrierintelligence.com/professors/jennifer-beane A computational biologist who develops and applies genomic methods to understand early lung cancer development. Her group analyzes bulk and single-cell RNA sequencing, spatial transcriptomics, and pathology images from the smoking-injured airway to find molecular markers that predict lung cancer risk and candidates for preventive therapy. - Departments: Medicine, School of Medicine - Research topics: ML Theory, Healthcare, Data Science - Email: jbeane@bu.edu - Website: https://www.bu.edu/hic/profile/jennifer-beane-ebel/ - Last verified: 2026-08-22 ### John Baillieul https://terrierintelligence.com/professors/john-baillieul A control theorist and roboticist who studies the mathematics of controlling mechanical systems, from nonlinear and networked control to communication-constrained robotics. His recent work develops neuromimetic control, analyzing how animals perceive and move in order to design perception and decision-making algorithms for autonomous vehicles and robots. - Departments: Mechanical Engineering, Electrical & Computer Engineering, College of Engineering - Research topics: Robotics - Email: johnb@bu.edu - Website: https://www.bu.edu/eng/profile/john-baillieul-ph-d-me-se/ - Last verified: 2026-08-22 ### John Liagouris https://terrierintelligence.com/professors/john-liagouris A systems researcher who builds distributed data processing systems with strong security and privacy guarantees. He co-leads a lab developing platforms for secure collaborative analytics, including Secrecy, a system that lets multiple organizations run computations over combined data using cryptographic protocols without revealing their private inputs. - Departments: Computer Science, College of Arts and Sciences - Research topics: ML Theory, Healthcare, Neuroscience, Data Science - Email: liagos@bu.edu - Website: https://www.bu.edu/hic/profile/john-liagouris/ - Last verified: 2026-08-22 ### Jonathan Huggins https://terrierintelligence.com/professors/jonathan-huggins A statistician and machine learning researcher who develops scalable Bayesian inference methods with trustworthy uncertainty quantification, even when models are imperfect and inference is approximate. His group builds computational tools applied to large-scale ecological forecasting and to scientific discovery from high-throughput, multi-modal genomic data. - Departments: Mathematics & Statistics, College of Arts and Sciences - Research topics: ML Theory, Healthcare, Data Science, Statistics - Email: huggins@bu.edu - Website: https://www.bu.edu/cds-faculty/profile/huggins/ - Last verified: 2026-08-22 ### Jonathan Jay https://terrierintelligence.com/professors/jonathan-jay A public health researcher who studies urban gun violence, particularly youth exposure, using machine learning, satellite imagery, and spatial analysis to identify block-level risk factors. His work evaluates place-based interventions such as building demolitions and vacant-lot improvements as strategies for reducing firearm injuries and racial disparities. - Departments: Community Health Sciences, School of Public Health - Research topics: ML Theory, Healthcare, Data Science, Statistics - Email: jonjay@bu.edu - Website: https://www.bu.edu/hic/profile/jonathan-jay/ - Last verified: 2026-08-22 ### Joshua Campbell https://terrierintelligence.com/professors/joshua-campbell A computational biologist who develops Bayesian methods and software for analyzing single-cell and spatial omics data and mutational signatures in cancer. His lab applies these tools to precancerous lung lesions and prostate cancer disparities, generating multi-omic datasets from patient samples to uncover mechanisms of tumor development. - Departments: Medicine, School of Medicine - Research topics: ML Theory, Healthcare, Data Science, Statistics - Email: camp@bu.edu - Website: https://www.bu.edu/cds-faculty/profile/joshua-campbell/ - Last verified: 2026-08-22 ### Juan Fuxman Bass https://terrierintelligence.com/professors/juan-fuxman-bass A systems biologist who studies how human gene regulatory networks control immune responses, cell differentiation, and viral pathogenesis. His lab integrates high-throughput screening, including an enhanced yeast one-hybrid platform testing over a thousand transcription factors, with bioinformatics analysis to map which factors regulate which genes. - Departments: Biology, College of Arts and Sciences - Research topics: ML Theory, Healthcare, Physical Sciences - Email: fuxman@bu.edu - Website: https://www.bu.edu/hic/profile/juan-fuxman-bass/ - Last verified: 2026-08-22 ### Julie Dahlstrom https://terrierintelligence.com/professors/julie-dahlstrom A legal scholar whose research examines how human trafficking law in the United States has evolved and how litigators mobilize it, including its expanding reach across federal and state statutes. She directs a clinical program in which law students represent immigrants and trafficking survivors in real cases. - Departments: Law, School of Law - Research topics: ML Theory, Data Science, Security, AI Safety - Email: jadahl@bu.edu - Website: https://www.bu.edu/hic/profile/julie-dahlstrom/ - Last verified: 2026-08-22 ### Kaija Schilde https://terrierintelligence.com/professors/kaija-schilde A political scientist who studies the political economy of security, asking why states outsource security to firms and markets. Her work examines defense industries, military spending, and the relationship between spending, innovation, and capabilities, with a focus on the European Union and transatlantic security institutions. - Departments: Pardee School of Global Studies - Research topics: ML Theory, Data Science, Social Science, Security - Email: kschilde@bu.edu - Website: https://www.bu.edu/hic/profile/kaija-schilde/ - Last verified: 2026-08-22 ### Kamal Sen https://terrierintelligence.com/professors/kamal-sen A computational neuroscientist who studies how the brain encodes and separates natural sounds, focusing on the cortical basis of auditory scene analysis. His lab combines neural recordings with information theory and signal processing, and develops brain-inspired algorithms for the cocktail party problem to improve hearing assistive devices. - Departments: Biomedical Engineering, College of Engineering - Research topics: ML Theory, Healthcare, Neuroscience, Data Science - Email: kamalsen@bu.edu - Website: https://www.bu.edu/eng/profile/kamal-sen-ph-d/ - Last verified: 2026-08-22 ### Katya Ravid https://terrierintelligence.com/professors/katya-ravid A molecular biologist who studies how bone marrow megakaryocytes develop into platelets, including the cell cycle control behind polyploidization, and how adenosine receptors shape vascular regeneration in injury and atherosclerosis. She also directs a university office fostering interdisciplinary biomedical research collaborations across BU's campuses. - Departments: Medicine, School of Medicine - Research topics: ML Theory, Healthcare, Data Science, Social Science - Email: kravid@bu.edu - Website: https://www.bu.edu/hic/profile/katya-ravid/ - Last verified: 2026-08-22 ### Keith Brown https://terrierintelligence.com/professors/keith-brown A materials researcher who develops self-driving laboratories that combine robotics, additive manufacturing, and machine learning to increase the pace and scale of experimentation. His group studies polymers and smart fluids to learn how useful properties emerge from composition, processing, and hierarchical structure. - Departments: Mechanical Engineering, College of Engineering - Research topics: ML Theory, Robotics, Data Science, Physical Sciences - Email: brownka@bu.edu - Website: https://www.bu.edu/eng/profile/keith-brown/ - Last verified: 2026-08-22 ### Kenn Sebesta https://terrierintelligence.com/professors/kenn-sebesta A robotics engineer with a controls background who directs BU's hands-on robotics teaching center, where students design, build, and test real robotic systems. Through courses and a tiered microcredential program, students can practice skills in automation, autonomous systems, and robot design. - Departments: Mechanical Engineering - Research topics: Robotics - Email: ksebesta@bu.edu - Website: https://www.bu.edu/eng/profile/kenn-sebesta/ - Last verified: 2026-08-22 ### Kia Teymourian https://terrierintelligence.com/professors/kia-teymourian A computer scientist who studies data stream and complex event processing, big data systems, and natural language processing. Recent work develops machine-learning models that predict heat transfer and air-pollutant dispersion over urban environments, and he teaches courses in data analysis and visualization. - Departments: Computer Science, Metropolitan College - Research topics: ML Theory, NLP/LLMs, Robotics, Healthcare - Email: kiat@bu.edu - Website: https://www.bu.edu/hic/profile/kia-teymourian/ - Last verified: 2026-08-22 ### Kirill Korolev https://terrierintelligence.com/professors/kirill-korolev A biophysicist who uses mathematical modeling to understand evolution and population dynamics in microbial communities, expanding populations, and cancer progression. His work draws on statistical physics and stochastic processes, combining analytical theory with computational analysis to ask how cooperation, competition, and spatial structure shape ecosystems. - Departments: Physics, College of Arts and Sciences - Research topics: ML Theory, Healthcare, Data Science, Physical Sciences - Email: korolev@bu.edu - Website: https://www.bu.edu/hic/profile/kirill-korolev/ - Last verified: 2026-08-22 ### Konstantinos Spiliopoulos https://terrierintelligence.com/professors/konstantinos-spiliopoulos An applied mathematician whose research develops algorithmic and computational methods for machine learning, including mean-field analysis of neural networks and uncertainty quantification in deep learning. He also studies stochastic processes, multiscale methods, and large deviations, with applications in financial mathematics and statistical network modeling. - Departments: Mathematics & Statistics, College of Arts and Sciences - Research topics: ML Theory, Data Science, Physical Sciences, Economy - Email: kspiliop@bu.edu - Website: https://www.bu.edu/hic/profile/konstantinos-spiliopoulos/ - Last verified: 2026-08-22 ### Laurina Zhang https://terrierintelligence.com/professors/laurina-zhang An economist of innovation who examines how technology and information access shape innovative, entrepreneurial, and creative outcomes, particularly for disadvantaged groups. Her empirical research studies the organizational and policy levers that affect innovation and inequality, spanning questions of digitization and democratized participation in creative work. - Departments: Strategy & Innovation, College of Arts and Sciences - Research topics: ML Theory, Data Science, Social Science - Email: laurinaz@bu.edu - Website: https://www.bu.edu/questrom/profiles/laurina-zhang/ - Last verified: 2026-08-22 ### Lei Tian https://terrierintelligence.com/professors/lei-tian A computational imaging researcher who jointly designs optics and algorithms, applying deep learning to biomedical microscopy and neurophotonics. His group builds methods such as differential phase contrast microscopy, Fourier ptychography, and imaging through scattering media, using neural networks to reconstruct and digitally label large-scale microscopy data. - Departments: Electrical and Computer Engineering, College of Engineering - Research topics: ML Theory, Data Science, Physical Sciences - Email: leitian@bu.edu - Website: https://www.bu.edu/eng/profile/lei-tian/ - Last verified: 2026-08-22 ### Lou Chitkushev https://terrierintelligence.com/professors/lou-chitkushev A computer scientist whose research spans health informatics, network security, and data assurance across healthcare, biomedical, and financial information systems. He co-founded BU's center for reliable information systems and cybersecurity, founded its health informatics program, and teaches medical informatics, computer networks, and network security. - Departments: Computer Science, Metropolitan College - Research topics: ML Theory, Computer Vision, NLP/LLMs, Healthcare - Email: LTC@bu.edu - Website: https://www.bu.edu/met/profile/lou-chitkushev/ - Last verified: 2026-08-22 ### Lucy Hutyra https://terrierintelligence.com/professors/lucy-hutyra An urban ecologist who studies the carbon cycle in cities, asking how urbanization alters vegetation, greenhouse gas emissions, and carbon uptake. Her group combines remote sensing, atmospheric observations, and ecological models on large NASA projects to quantify urban emissions and inform sustainability planning. - Departments: Earth & Environment, College of Arts and Sciences - Research topics: ML Theory, Healthcare, Statistics, Physical Sciences - Email: lrhutyra@bu.edu - Website: https://www.bu.edu/earth/profiles/lucy-hutyra/ - Last verified: 2026-08-22 ### Ludovic Trinquart https://terrierintelligence.com/professors/ludovic-trinquart A biostatistician and clinical trial methodologist whose work improves the design, analysis, and interpretation of randomized trials. His research develops methods for time-to-event outcomes, meta-analysis, and patient-centered measures of treatment effect, collaborating with clinical investigators across oncology, cardiology, and population health. - Departments: Biostatistics, School of Public Health - Research topics: ML Theory, Healthcare, Statistics - Email: ludovic@bu.edu - Website: https://www.bu.edu/hic/profile/ludovic-trinquart/ - Last verified: 2026-08-22 ### Luis Carvalho https://terrierintelligence.com/professors/luis-carvalho A statistician who develops Bayesian methods for statistical inference in structured, high-dimensional discrete spaces, together with computational statistics and network modeling. Applications include land-cover classification from satellite imagery, gene-interaction analysis in genome-wide association studies, and community detection in social networks. - Departments: Mathematics & Statistics, College of Arts & Sciences - Research topics: ML Theory, Healthcare, Data Science, Statistics - Email: lecarval@bu.edu - Website: https://www.bu.edu/hic/profile/luis-carvalho/ - Last verified: 2026-08-22 ### Maggie Mulvihill https://terrierintelligence.com/professors/maggie-mulvihill An investigative journalist who applies computational and data-driven reporting methods to government accountability stories. She developed BU journalism's first data journalism course and has trained hundreds of journalists in data storytelling; students in her courses can practice data analysis and data-driven storytelling for investigative work. - Departments: Journalism, College of Communication - Research topics: ML Theory, Data Science, Social Science, Humanities - Email: mmulvih@bu.edu - Website: https://www.bu.edu/com/profile/maggie-mulvihill/ - Last verified: 2026-08-22 ### Marc Howard https://terrierintelligence.com/professors/marc-howard A theoretical cognitive neuroscientist who develops mathematical models of memory and evaluates them against behavioral and neurophysiological data. His lab studies how the brain represents time and space to support episodic memory, bridging cognition and systems neuroscience through mathematical, computational, and behavioral tools. - Departments: Psychological and Brain Sciences, College of Arts and Sciences - Research topics: ML Theory, Neuroscience - Email: marc777@bu.edu - Website: https://www.bu.edu/hic/profile/marc-howard/ - Last verified: 2026-08-22 ### Marc Lenburg https://terrierintelligence.com/professors/marc-lenburg A computational biologist who uses genomic approaches to understand how tobacco smoke alters airway biology and drives diseases such as lung cancer and chronic obstructive pulmonary disease. His work translates gene-expression findings into diagnostics, including a nasal swab genomic test for assessing suspicious lung nodules. - Departments: Medicine, School of Medicine - Research topics: ML Theory, Healthcare, Data Science, Statistics - Email: mlenburg@bu.edu - Website: https://www.bu.edu/hic/profile/marc-lenburg/ - Last verified: 2026-08-22 ### Marc Rysman https://terrierintelligence.com/professors/marc-rysman An empirical industrial organization economist who studies network effects, platform markets, and standardization, with attention to the antitrust and regulatory questions they raise. His research spans payment cards, telecommunications, and consumer electronics, and his teaching covers industrial organization, econometrics, and antitrust policy. - Departments: Economics, College of Arts and Sciences - Research topics: ML Theory, Data Science, Physical Sciences, Social Science - Email: mrysman@bu.edu - Website: https://www.bu.edu/hic/profile/marc-rysman/ - Last verified: 2026-08-22 ### Marco Gaboardi https://terrierintelligence.com/professors/marco-gaboardi A programming-languages researcher who builds formal methods and type systems for verifying differential privacy, producing mechanized proofs that data analyses protect individual records while staying accurate. He mentors PhD students and postdoctoral researchers and teaches courses on formal methods in security and privacy. - Departments: Computer Science, College of Arts and Sciences - Research topics: ML Theory, Data Science, Social Science, Economy - Email: gaboardi@bu.edu - Website: https://www.bu.edu/cs/profiles/gaboardi/ - Last verified: 2026-08-22 ### Marianne Baxter https://terrierintelligence.com/professors/marianne-baxter A macroeconomist whose research examines economic fluctuations, the international transmission of business cycles, and pricing in international settings. Her empirical and theoretical work includes estimating exchange rate pass-through, analyzing price-setting behavior in monopolistic international markets, and testing asset pricing models with panel data. - Departments: Economics, College of Arts and Sciences - Research topics: ML Theory, Data Science, Physical Sciences, Social Science - Email: mbaxter@bu.edu - Website: https://www.bu.edu/hic/profile/marianne-baxter/ - Last verified: 2026-08-22 ### Mark Crovella https://terrierintelligence.com/professors/mark-crovella A computer scientist who applies data mining, statistics, and performance evaluation to the understanding and design of networks and networked computer systems. His work spans Internet measurement, traffic analysis, and anomaly detection, and extends network-analysis methods to social and biological networks. - Departments: Computer Science, College of Arts and Sciences - Research topics: ML Theory, Healthcare, Data Science, Environment - Email: crovella@bu.edu - Website: https://www.bu.edu/cs/profiles/crovella/ - Last verified: 2026-08-22 ### Mark Kon https://terrierintelligence.com/professors/mark-kon A mathematician whose research develops machine learning theory, statistical learning, and quantum probability and information, with applications in bioinformatics and computational neuroscience. He co-leads BU's Stochastic Machine Learning Group, where graduate and undergraduate students work on theoretical and applied problems in data analysis and prediction. - Departments: Mathematics & Statistics, College of Arts & Sciences - Research topics: ML Theory, Computer Vision, Healthcare, Neuroscience - Email: mkon@bu.edu - Website: https://www.bu.edu/hic/profile/mark-kon/ - Last verified: 2026-08-22 ### Mark Kramer https://terrierintelligence.com/professors/mark-kramer A mathematical neuroscientist who builds biophysical models of neural activity and develops data analysis methods for brain recordings. His work characterizes the brain patterns seen during epileptic seizures, aiming to help clinicians identify which brain regions and mechanisms to target when treating epilepsy. - Departments: Mathematics & Statistics, College of Arts and Sciences - Research topics: ML Theory, Healthcare, Neuroscience, Data Science - Email: mak@bu.edu - Website: https://www.bu.edu/hic/profile/mark-kramer/ - Last verified: 2026-08-22 ### Marshall Van Alstyne https://terrierintelligence.com/professors/marshall-van-alstyne An information economist who studies how networks and platforms create value, developing theory of two-sided markets and platform business models that has been applied in antitrust analysis. He also designs market mechanisms, such as truth warrants, to combat misinformation and improve information quality online. - Departments: Information Systems, Questrom School of Business - Research topics: ML Theory, Computer Vision, NLP/LLMs, Data Science - Email: mva@bu.edu - Website: https://www.bu.edu/questrom/profiles/marshall-van-alstyne/ - Last verified: 2026-08-22 ### Martin Fiszbein https://terrierintelligence.com/professors/martin-fiszbein An economist whose research examines economic growth and development, economic history, and urban economics, with a focus on historical political economy and historical development. His work uses evidence from history to study how economies grow over the long run, and he is a National Bureau of Economic Research associate. - Departments: Economics, College of Arts and Sciences - Research topics: ML Theory, Data Science, Physical Sciences, Social Science - Email: fiszbein@bu.edu - Website: https://www.bu.edu/hic/profile/martin-fiszbein/ - Last verified: 2026-08-22 ### Martin Herbordt https://terrierintelligence.com/professors/martin-herbordt A computer engineer who designs high-performance computing systems using hardware accelerators, particularly field-programmable gate arrays and graphics processing units. His research applies these architectures to problems in bioinformatics and computational biology, and he teaches courses in computer organization, computer architecture, and high-performance programming. - Departments: Electrical and Computer Engineering, College of Engineering - Research topics: ML Theory, Healthcare, Physical Sciences, Security - Email: herbordt@bu.edu - Website: https://www.bu.edu/eng/profile/martin-herbordt/ - Last verified: 2026-08-22 ### Mary Dunlop https://terrierintelligence.com/professors/mary-dunlop A biomedical engineer who combines synthetic biology, feedback control, and deep learning to study and engineer microbial systems. Her lab applies optogenetics and single-cell microscopy to problems including antibiotic resistance and metabolic engineering, and she has received BU awards for teaching and postdoc mentoring. - Departments: Biomedical Engineering, College of Engineering - Research topics: ML Theory, Healthcare - Email: mjdunlop@bu.edu - Website: https://www.bu.edu/eng/profile/mary-dunlop-ph-d/ - Last verified: 2026-08-22 ### Mohammad Soltanieh Ha https://terrierintelligence.com/professors/mohammad-soltanieh-ha A data scientist with a computational physics background whose research explores embodied AI, interactive avatars, and socially impactful applications of large language models. He teaches courses spanning big data analytics, cloud computing, and Python and R programming, and advocates for integrating data science into undergraduate curricula. - Departments: Information Systems, Questrom School of Business - Research topics: ML Theory, Robotics, Healthcare, Data Science - Email: msoltani@bu.edu - Website: https://www.bu.edu/questrom/profiles/mohammad-soltaniehha/ - Last verified: 2026-08-22 ### Nachiketa Sahoo https://terrierintelligence.com/professors/nachiketa-sahoo A machine-learning and information-systems researcher who studies how user preferences and decision processes can be learned from large-scale activity data to improve personalized recommendations. His work applies recommender systems and statistical models to e-commerce, digital media, and philanthropic giving, and he helped design the school's business analytics master's program. - Departments: Information Systems, Questrom School of Business - Research topics: ML Theory, Data Science, Social Science, Policy - Email: nachi@bu.edu - Website: https://www.bu.edu/questrom/profiles/nachiketa-sahoo/ - Last verified: 2026-08-22 ### Nicholas Crossland https://terrierintelligence.com/professors/nicholas-crossland A pathologist who investigates how highly pathogenic microbes interact with their hosts, combining classical pathology with spatial transcriptomics, quantitative image analysis, and deep learning-based spatial immunoprofiling. His lab evaluates medical countermeasures against infectious diseases such as tuberculosis and filovirus infection, and he mentors master's and PhD students. - Departments: Pathology and Laboratory Medicine, School of Medicine - Research topics: ML Theory, Healthcare - Email: ncrossla@bu.edu - Website: https://www.bu.edu/hic/profile/nicholas-crossland/ - Last verified: 2026-08-22 ### Nicholas Wagner https://terrierintelligence.com/professors/nicholas-wagner A developmental psychologist who examines how early experiences and self-regulation shape children's social and emotional development from infancy to early adolescence. His lab measures development at behavioral, experiential, and biological levels, studying outcomes from empathy to callous-unemotional traits, and undergraduate and graduate students assist with its research. - Departments: Psychological and Brain Sciences, College of Arts and Sciences - Research topics: ML Theory, Healthcare, Neuroscience, Statistics - Email: njwagner@bu.edu - Website: https://www.bu.edu/hic/profile/nicholas-wagner/ - Last verified: 2026-08-22 ### Noora Lori https://terrierintelligence.com/professors/noora-lori A political scientist whose research examines citizenship and forced migration in the Middle East, showing how states can hold residents in prolonged temporary status without citizenship rights. Her book Offshore Citizens studies the United Arab Emirates, and she directs the Initiative on Forced Migration and Human Trafficking. - Departments: International Relations, Pardee School of Global Studies - Research topics: ML Theory, Healthcare, Data Science, Statistics - Email: nlori@bu.edu - Website: https://www.bu.edu/hic/profile/noora-lori/ - Last verified: 2026-08-22 ### Orkun Baycik https://terrierintelligence.com/professors/orkun-baycik An operations researcher who applies machine learning, optimization, and prescriptive analytics to modeling and disrupting illegal supply chains, digital transformation of operations, and data analytics for nonprofits. He teaches business analytics courses, including spreadsheet optimization, simulation, and causal methods for business experiments. - Departments: Markets, Public Policy, and Law, Questrom School of Business - Research topics: ML Theory, Data Science, Physical Sciences - Email: nobaycik@bu.edu - Last verified: 2026-08-22 ### Pankaj Mehta https://terrierintelligence.com/professors/pankaj-mehta A theoretical physicist working at the interface of statistical physics, machine learning, and biology. He studies how cell fates emerge from biomolecular interactions, ecological principles in microbial communities, and the theory of learning, and develops new ML methods for analyzing biological data. - Departments: Physics, College of Arts and Sciences - Research topics: ML Theory, Healthcare, Neuroscience, Data Science - Email: pankajm@bu.edu - Website: https://www.bu.edu/cds-faculty/profile/pankaj-mehta/ - Last verified: 2026-08-22 ### Paola Sebastiani https://terrierintelligence.com/professors/paola-sebastiani A biostatistician who develops Bayesian modeling and machine-learning methods for genetic and genomic data, dissecting the biological basis of complex traits. Her work includes network models predicting complications of sickle cell anemia and long-running statistical studies of human longevity, including the New England Centenarian Study. - Departments: Biostatistics, College of Arts and Sciences - Research topics: ML Theory, Healthcare, Data Science, Statistics - Email: sebas@bu.edu - Last verified: 2026-08-22 ### Pary Fassihi https://terrierintelligence.com/professors/pary-fassihi A writing instructor whose work examines how generative AI tools can support academic writing instruction and AI literacy. She teaches AI-intensive writing courses, develops flipped-learning modules and other digital course materials, and serves on the Provost's AI Task Force, exploring generative AI activities in the classroom. - Departments: Writing Program - Research topics: Generative AI/Tools, Ethics, Education - Email: fassihi@bu.edu - Website: https://www.bu.edu/writingprogram/profile/pary-fassihi/ - Last verified: 2026-08-22 ### Patricia Fabian https://terrierintelligence.com/professors/patricia-fabian An environmental health researcher who studies how the built environment shapes health disparities, combining systems science models, geographic information system mapping, and high-resolution sensor data. Her projects link housing conditions, indoor air quality, and energy use to health, informing climate resilience efforts in Boston schools and frontline communities. - Departments: Environmental Health, School of Public Health - Research topics: ML Theory, Computer Vision, NLP/LLMs, Healthcare - Email: pfabian@bu.edu - Last verified: 2026-08-22 ### Paul Carlile https://terrierintelligence.com/professors/paul-carlile An organizational scholar who examines the knowledge boundaries that separate people in different expertise domains and how they can be crossed to enhance collaboration and innovation. His work spans product development in industries such as automotive, software, and pharmaceuticals, along with studies of data-driven practices in healthcare organizations. - Departments: Information Systems, Questrom School of Business - Research topics: ML Theory, Data Science - Email: carlile@bu.edu - Website: https://www.bu.edu/questrom/profiles/paul-carlile/ - Last verified: 2026-08-22 ### Peixi Liao https://terrierintelligence.com/professors/peixi-liao A prosthodontics researcher focused on digital dentistry, developing data-driven diagnostic approaches and virtual simulation technologies for restorative treatment planning. He has founded and taught courses on digital dentistry in prosthodontics and restorative science, and serves as president of the International Association for Dental Research's Prosthodontics Group. - Departments: Department of Restorative Sciences and Biomaterials, Goldman School of Dental Medicine - Research topics: ML Theory, Robotics, Physical Sciences - Email: liaopx@bu.edu - Last verified: 2026-08-22 ### Peter Blake https://terrierintelligence.com/professors/peter-blake A developmental psychologist who studies how children come to understand the social world, running cognitive and behavioral experiments with children ages two to twelve on fairness, cooperation, and ownership. He collaborates with game theorists and anthropologists and compares social development across cultures to identify common patterns. - Departments: Psychological & Brain Sciences, College of Arts and Sciences - Research topics: ML Theory, Healthcare, Neuroscience, Data Science - Email: pblake@bu.edu - Website: https://www.bu.edu/hic/profile/peter-blake/ - Last verified: 2026-08-22 ### Qiang Cui https://terrierintelligence.com/professors/qiang-cui A theoretical and computational chemist who develops and applies multiscale simulation methods, including quantum mechanics/molecular mechanics and coarse-grained models, to chemical and biological problems. His group studies enzyme catalysis, biological membrane remodeling, and the nano-bio interface, with an emphasis on processes spanning multiple length and time scales. - Departments: Chemistry, College of Arts and Sciences - Research topics: ML Theory, Healthcare, Data Science, Physical Sciences - Email: qiangcui@bu.edu - Website: https://www.bu.edu/eng/profile/qiang-cui-ph-d/ - Last verified: 2026-08-22 ### Reza Rawassizadeh https://terrierintelligence.com/professors/reza-rawassizadeh A computer scientist who builds resource-efficient machine learning algorithms for battery-powered devices such as smartwatches, fitness trackers, and small robots. His work enables models to run entirely on-device, without cloud infrastructure or network connections, supporting applications in digital health and ubiquitous computing. - Departments: Computer Science - Research topics: ML Theory, Healthcare - Email: rezar@bu.edu - Website: https://www.bu.edu/met/profile/reza-rawassizadeh/ - Last verified: 2026-08-22 ### Rhoda Au https://terrierintelligence.com/professors/rhoda-au A neuropsychologist who develops digital biomarkers for cognitive aging, applying voice analysis and other sensor technologies to detect early signs of dementia. As a principal investigator of the Framingham Heart Study Brain Aging Program, she works to build scalable, technology-agnostic platforms for monitoring brain health across populations. - Departments: Anatomy and Neurobiology, School of Medicine - Research topics: ML Theory, Healthcare, Neuroscience, Data Science - Email: rhodaau@bu.edu - Website: https://www.bu.edu/hic/profile/rhoda-au/ - Last verified: 2026-08-22 ### Roscoe Giles https://terrierintelligence.com/professors/roscoe-giles A computational scientist whose research applies high-performance and parallel computing to physics and materials problems, from quantum field theory to simulations of magnetic materials. He currently focuses on helping AI and ML research and education communities gain improved access to large-scale high-performance computing systems. - Departments: Electrical and Computer Engineering, College of Engineering - Research topics: ML Theory, Physical Sciences - Email: roscoe@bu.edu - Website: https://www.bu.edu/eng/profile/roscoe-giles/ - Last verified: 2026-08-22 ### Samuel Bazzi https://terrierintelligence.com/professors/samuel-bazzi A development economist whose research examines migration, culture, and political economy, asking how individuals and nations adapt to diversity in a globalized world. He applies econometric methods to study labor mobility, the cultural effects of migration, and the links between economic shocks and conflict. - Departments: Economics, College of Arts and Sciences - Research topics: ML Theory, Data Science, Physical Sciences, Social Science - Email: sbazzi@bu.edu - Last verified: 2026-08-22 ### Sarah Bargal https://terrierintelligence.com/professors/sarah-bargal A machine learning and computer vision researcher whose work focuses on making AI systems explainable and accountable to humans and society. Her research spans image and video understanding and the interpretability of deep neural networks, and she has co-directed the AI4ALL program at BU. - Departments: Computer Science, College of Arts and Sciences - Research topics: ML Theory, Neuroscience, Data Science, Humanities - Email: sbargal@bu.edu - Last verified: 2026-08-22 ### Sarah Frederick https://terrierintelligence.com/professors/sarah-frederick A scholar of modern Japanese literature whose work examines mass media, gender, and print culture, with a focus on interwar women's magazines. Her digital humanities projects apply geographic information system mapping to literary texts, including a collaborative effort charting writers' travels through Kyoto. - Departments: World Languages and Comparative Literature, College of Arts and Sciences - Research topics: ML Theory, Computer Vision, NLP/LLMs, Data Science - Email: sfred@bu.edu - Website: https://www.bu.edu/hic/profile/sarah-frederick/ - Last verified: 2026-08-22 ### Scott Hirst https://terrierintelligence.com/professors/scott-hirst A corporate law scholar whose empirical research examines corporate governance, shareholder voting, and the influence of index funds and institutional investors. He combines quantitative evidence with concepts from finance, accounting, and economics to explain how corporations and investors make decisions and to inform policy making. - Departments: School of Law - Research topics: ML Theory, Data Science, Physical Sciences, Social Science - Email: hirst@bu.edu - Website: https://www.bu.edu/hic/profile/scott-hirst/ - Last verified: 2026-08-22 ### Sean B. Andersson https://terrierintelligence.com/professors/sean-b-andersson A systems and control researcher whose work spans robotics and nanobioscience. He develops feedback control and estimation methods for real-time single-particle tracking microscopy, which keep individual nanometer-scale particles inside a microscope's detection volume, and applies related control and estimation techniques to problems in robotics. - Departments: Mechanical Engineering, College of Engineering - Research topics: Robotics - Email: sanderss@bu.edu - Website: https://www.bu.edu/hic/profile/sean-b-andersson/ - Last verified: 2026-08-22 ### Selim Ünlü https://terrierintelligence.com/professors/selim-unlu A photonics researcher who develops optical imaging and biosensing techniques, including interferometric reflectance sensors that detect individual viruses, nanoparticles, and single molecules without labels. His work applies high-resolution microscopy to biological diagnostics and to imaging semiconductor devices and integrated circuits. - Departments: ECE, BME, MSE, College of Engineering - Research topics: ML Theory, Physical Sciences - Email: selim@bu.edu - Website: https://www.bu.edu/eng/profile/selim-unlu/ - Last verified: 2026-08-22 ### Shanshan Sheehy https://terrierintelligence.com/professors/shanshan-sheehy An epidemiologist whose research examines cardiometabolic health, pregnancy complications, and health disparities, largely through prospective cohort studies such as the Black Women's Health Study. She analyzes genetic, clinical, and survey data to identify risk factors for cardiovascular disease, stroke, and Alzheimer's disease among African American women. - Departments: Slone Epidemiology Center, School of Medicine - Research topics: ML Theory, Computer Vision, NLP/LLMs, Healthcare - Email: shl607@bu.edu - Website: https://www.bu.edu/hic/profile/shanshan-sheehy/ - Last verified: 2026-08-22 ### Shariq Mohammed https://terrierintelligence.com/professors/shariq-mohammed A biostatistician who develops methods combining hierarchical Bayesian modeling, variable selection, and spatial statistics for complex biomedical data. His group applies these tools to imaging, spatial-omics, and digital health datasets, addressing questions in oncology and in neurodegenerative conditions such as Alzheimer's disease and dementia. - Departments: Biostatistics, School of Public Health - Research topics: ML Theory, Healthcare, Neuroscience, Statistics - Email: shariqm@bu.edu - Website: https://www.bu.edu/hic/profile/shariq-mohammad/ - Last verified: 2026-08-22 ### Sheila Russo https://terrierintelligence.com/professors/sheila-russo A surgical robotics researcher who designs miniaturized soft robots for minimally invasive procedures. Her group combines soft materials, sensing and actuation, and meso- and micro-scale manufacturing to build flexible surgical instruments, including robotic systems for diagnosing and treating lung cancer inside the body. - Departments: Mechanical Engineering, Materials Science and Engineering, College of Engineering - Research topics: Robotics - Email: russos@bu.edu - Website: https://www.bu.edu/eng/profile/sheila-russo-phd/ - Last verified: 2026-08-22 ### Shengzhi Zhang https://terrierintelligence.com/professors/shengzhi-zhang A computer security researcher whose work examines how attackers compromise modern computing platforms and how to defend them. He studies AI security alongside the security of Internet of Things devices, automobiles, and operating systems, analyzing vulnerabilities in these systems and developing practical protections. - Departments: Computer Science, Metropolitan College - Research topics: Robotics, Security - Email: shengzhi@bu.edu - Website: https://www.bu.edu/met/profile/shengzhi-zhang/ - Last verified: 2026-08-22 ### Sheryl Grace https://terrierintelligence.com/professors/sheryl-grace An aerospace engineering researcher who studies unsteady aerodynamics and aeroacoustics, the physics of noise generated by airflow. Her group develops and benchmarks computational fluid dynamics approaches for predicting fan noise in aircraft engines and examines inverse methods that identify noise sources from measured acoustic data. - Departments: Mechanical Engineering, College of Engineering - Research topics: ML Theory, Robotics, Physical Sciences - Email: sgrace@bu.edu - Website: https://www.bu.edu/eng/profile/sheryl-grace-ph-d/ - Last verified: 2026-08-22 ### Simone Gill https://terrierintelligence.com/professors/simone-gill A movement scientist who studies how walking and motor function change across the lifespan, focusing on how obesity affects gait and fall risk. Her Motor Development Laboratory analyzes movement with three-dimensional motion capture, wearable sensors, and digital pressure mats, including studies of patients before and after bariatric surgery. - Departments: Occupational Therapy, Sargent College - Research topics: ML Theory, Healthcare, Neuroscience, Data Science - Email: simvgill@bu.edu - Website: https://www.bu.edu/hic/profile/simone-gill/ - Last verified: 2026-08-22 ### Sophie Hao https://terrierintelligence.com/professors/sophie-hao A computational linguist whose research develops interpretability methods for natural language processing, working toward a science of deep neural language models. Her group studies how models represent linguistic structure, using probing, feature attribution, and formal analysis of neural architectures, with attention to bias and fairness. - Departments: Linguistics, Computing & Data Sciences, College of Arts & Sciences, CDS - Research topics: ML Theory, NLP/LLMs, Ethics - Email: hao@bu.edu - Website: https://www.bu.edu/linguistics/profile/sophie-hao/ - Last verified: 2026-08-22 ### Stephen Grossberg https://terrierintelligence.com/professors/stephen-grossberg A theoretical neuroscientist who models how the brain learns to attend, categorize, and predict events in a changing world. He co-developed Adaptive Resonance Theory, a family of neural network models that learn incrementally without erasing prior memories and are applied to pattern recognition and prediction. - Departments: Mathematics and Statistics, Psychological and Brain Sciences, Biomedical Engineering, College of Arts and Sciences - Research topics: ML Theory, NLP/LLMs, Robotics, Neuroscience - Email: steve@bu.edu - Website: https://www.bu.edu/eng/profile/stephen-grossberg-ph-d/ - Last verified: 2026-08-22 ### Sucharita Gopal https://terrierintelligence.com/professors/sucharita-gopal A geographer who applies neural networks and machine learning to remote sensing, geographic information systems, and spatial analysis. Her projects pair these methods with policy questions, including marine spatial planning in Massachusetts, malaria risk mapping in Ethiopia, and mapping health service delivery in Zambia. - Departments: Earth & Environment, College of Arts and Sciences - Research topics: Environment, Social Science, Policy - Email: suchi@bu.edu - Website: https://www.bu.edu/earth/profiles/sucharita-gopal/ - Last verified: 2026-08-22 ### Suresh Kalathur https://terrierintelligence.com/professors/suresh-kalathur A computer scientist focused on data analytics and analytics education who directs graduate analytics programs and helped establish a master's degree in applied data analytics. He teaches courses in analytics, data visualization, and server-side web development, and builds classroom tools that give students real-time feedback during lectures. - Departments: Computer Science, Metropolitan College - Research topics: ML Theory, Data Science, Environment, Social Science - Email: kalathur@bu.edu - Website: https://www.bu.edu/met/profile/suresh-kalathur/ - Last verified: 2026-08-22 ### Swathi Kiran https://terrierintelligence.com/professors/swathi-kiran A speech-language neuroscientist who studies how the brain recovers language after stroke, focusing on aphasia rehabilitation and bilingual language recovery. Her work combines neuroimaging, behavioral treatment studies, and computational modeling to predict rehabilitation outcomes, and she co-founded a digital therapy platform that uses machine learning to personalize exercises. - Departments: Speech, Language, and Hearing Sciences, Sargent College - Research topics: Computer Vision, NLP/LLMs, Healthcare, Neuroscience - Email: kirans@bu.edu - Website: https://www.bu.edu/cds-faculty/profile/swathi-kiran/ - Last verified: 2026-08-22 ### Taylor Boas https://terrierintelligence.com/professors/taylor-boas A comparative political scientist who studies electoral politics, public opinion, and political behavior in Latin America, with attention to religion, accountability, and mass media. He tests how voters respond to information using survey and field experiments, pre-registered designs, and cross-country meta-analyses, and teaches quantitative research methods. - Departments: Political Science, College of Arts and Sciences - Research topics: ML Theory, Data Science, Social Science, Policy - Email: tboas@bu.edu - Website: https://www.bu.edu/hic/profile/taylor-boas/ - Last verified: 2026-08-22 ### Terry Ellis https://terrierintelligence.com/professors/terry-ellis A neurorehabilitation researcher who studies walking impairments in people with Parkinson disease and develops interventions to improve real-world mobility. Her work applies wearable sensors, digital health technology, and soft robotic exosuits to measure gait and reduce freezing episodes, and she directs BU's Center for Neurorehabilitation. - Departments: Physical Therapy & Athletic Training, Sargent College - Research topics: ML Theory, Robotics, Healthcare - Email: tellis@bu.edu - Last verified: 2026-08-22 ### Tesary Lin https://terrierintelligence.com/professors/tesary-lin A quantitative marketing researcher who examines how data and privacy shape relationships between firms and consumers. Her work studies consumer privacy preferences and how privacy regulation, choice architecture, and algorithms affect digital markets and consumer welfare, informing analytics tools adapted to the modern information environment. - Departments: Marketing, Questrom School of Business - Research topics: ML Theory, Data Science, Social Science, Economy - Email: tesary@bu.edu - Website: https://www.bu.edu/questrom/profiles/tesary-lin/ - Last verified: 2026-08-22 ### Thomas Byrne https://terrierintelligence.com/professors/thomas-byrne A social welfare policy researcher who studies the causes, consequences, and policy solutions of homelessness and housing insecurity. His work applies quantitative and quasi-experimental methods to administrative data, examining how housing markets, prevention programs, and housing assistance shape homelessness rates and health outcomes, including among veterans. - Departments: Social Welfare Policy, School of Social Work - Research topics: ML Theory, Healthcare, Data Science, Statistics - Email: tbyrne@bu.edu - Last verified: 2026-08-22 ### Thomas Kepler https://terrierintelligence.com/professors/thomas-kepler A computational immunologist who develops mathematical and statistical tools to study antibody evolution and B-cell responses. His laboratory combines these methods with systems-level experiments to guide vaccine design, including computational selection of immunogens for candidate vaccines against HIV, influenza, and anthrax. - Departments: Microbiology Department, School of Medicine - Research topics: ML Theory, Healthcare, Data Science, Physical Sciences - Email: tbkepler@bu.edu - Last verified: 2026-08-22 ### Thomas Little https://terrierintelligence.com/professors/thomas-little A networking and communications researcher who develops technologies for smart, connected systems. His work spans optical wireless and visible-light communication, vehicular networks, and pervasive computing, and he directs BU's Multimedia Communications Laboratory, which builds enabling technologies and applications for interactive multimedia systems. - Departments: Electrical and Computer Engineering, College of Engineering - Research topics: Robotics, Environment - Email: tdcl@bu.edu - Website: https://www.bu.edu/eng/profile/thomas-little/ - Last verified: 2026-08-22 ### Tianyu Wang https://terrierintelligence.com/professors/tianyu-wang A computational imaging and photonics researcher who harnesses optical physics to build more efficient sensors and processors. His laboratory studies information processing in physical systems, developing photonic hardware for artificial neural networks and quantum-inspired light sources for deep-tissue imaging, with applications in sensing, communication, and AI computing. - Departments: Electrical and Computer Engineering, College of Engineering - Research topics: ML Theory, Healthcare, Neuroscience, Physical Sciences - Email: wangty@bu.edu - Website: https://www.bu.edu/eng/profile/tianyu-wang-phd/ - Last verified: 2026-08-22 ### Timothy Brown https://terrierintelligence.com/professors/timothy-brown A clinical psychologist whose work centers on the classification of anxiety and mood disorders, temperament, and psychopathology, alongside research methodology and psychometrics. He directs research at BU's Center for Anxiety and Related Disorders and teaches multivariate statistics, including structural equation and latent growth modeling. - Departments: Psychological and Brain Sciences, College of Arts and Sciences - Research topics: ML Theory, Healthcare, Statistics - Email: tabrown@bu.edu - Last verified: 2026-08-22 ### Ting Fang Alvin Ang https://terrierintelligence.com/professors/ting-fang-alvin-ang A physician-researcher who studies Alzheimer disease and traumatic brain injury through the Framingham Heart Study. His work manages and analyzes large longitudinal cohort data, applying conventional statistical and machine-learning techniques to improve understanding, clinical guidelines, and practice around neurocognitive disorders. - Departments: Anatomy & Neurobiology, School of Medicine - Research topics: ML Theory, Statistics - Email: alvinang@bu.edu - Website: https://www.bu.edu/hic/profile/ting-fang-alvin-ang/ - Last verified: 2026-08-22 ### Tommaso Ranzani https://terrierintelligence.com/professors/tommaso-ranzani A soft-robotics researcher who designs bioinspired robots that operate in complex environments, from minimally invasive surgery to underwater exploration. His Morphable Biorobotics Lab develops soft manipulators and wearable devices, including a soft robot that guides interventional tools inside the beating heart with an expandable stabilization mechanism. - Departments: Mechanical Engineering, Biomedical Engineering, and in the Division of Materials Science and Engineering, College of Engineering - Research topics: Robotics - Email: tranzani@bu.edu - Website: https://www.bu.edu/hic/profile/tommaso-ranzani/ - Last verified: 2026-08-22 ### Tugba Efendigil https://terrierintelligence.com/professors/tugba-efendigil A supply chain researcher who studies digital transformation and circular supply chains, designing forward and reverse flows that support agile, resilient operations. Her work applies technology and analytics to supply chain optimization, drawing on prior research experience at MIT and in industry. - Departments: Operations and Technology Management, Questrom School of Business - Research topics: ML Theory, Data Science, Environment - Email: tugbae@bu.edu - Website: https://www.bu.edu/questrom/profiles/tugba-efendigil/ - Last verified: 2026-08-22 ### Vijaya Kolachalama https://terrierintelligence.com/professors/vijaya-kolachalama A machine-learning and precision-medicine researcher who develops software frameworks that assist clinicians in real-world settings. His laboratory works on biomedical machine vision, multimodal representation learning, and domain generalization, including AI tools that support diagnosis of Alzheimer disease and related dementias. - Departments: Medicine, School of Medicine - Research topics: ML Theory, Healthcare, Neuroscience - Email: vkola@bu.edu - Website: https://www.bu.edu/cs/profiles/vkola/ - Last verified: 2026-08-22 ### Vipul Chitalia https://terrierintelligence.com/professors/vipul-chitalia A physician-scientist who studies vascular pathologies in cancer and renal failure, focusing on post-translational protein modifications such as polyubiquitination. His laboratory combines cellular and molecular biology, animal models, and computational and machine-learning methods, validating findings in humanized models and large human databases. - Departments: Medicine, School of Medicine - Research topics: ML Theory, Computer Vision, NLP/LLMs, Healthcare - Email: vichital@bu.edu - Website: https://www.bu.edu/hic/profile/vipul-chitalia/ - Last verified: 2026-08-22 ### Wei-Lun Chao https://terrierintelligence.com/professors/wei-lun-chao A machine-learning and computer-vision researcher who studies learning from imperfect data, including limited, noisy, and distribution-shifting sources. His work develops methods for federated learning and robust visual recognition that keep models reliable under such conditions, with applications spanning autonomous driving, biodiversity monitoring, and healthcare. - Departments: Electrical & Computer Engineering, College of Engineering - Research topics: Computer Vision - Email: weichao@bu.edu - Website: https://www.bu.edu/hic/2026-hariri-institute-junior-faculty-fellows-and-graduate-student-fellows/ - Last verified: 2026-08-22 ### Wen Li https://terrierintelligence.com/professors/wen-li A space physicist who studies plasma waves, Earth's radiation belts, and energetic particle precipitation in planetary magnetospheres, including Jupiter's. Her research combines satellite observations with physics-based modeling and machine-learning approaches to quantitatively assess radiation-belt electron dynamics and solar wind-magnetosphere coupling. - Departments: Astronomy, College of Arts and Sciences - Research topics: ML Theory, Physical Sciences, Environment - Email: wenli77@bu.edu - Website: https://www.bu.edu/hic/profile/wen-li/ - Last verified: 2026-08-22 ### Wenchao Li https://terrierintelligence.com/professors/wenchao-li A dependable-computing researcher whose work sits at the intersection of formal methods and machine learning, focusing on neuro-symbolic reasoning and the safety and trustworthiness of AI-driven autonomous systems. His laboratory develops computational proof techniques with applications from design automation to multi-robot systems and self-driving cars. - Departments: Electrical and Computer Engineering, College of Engineering - Research topics: ML Theory, Robotics, AI Safety - Email: wenchao@bu.edu - Website: https://www.bu.edu/hic/profile/wenchao-li/ - Last verified: 2026-08-22 ### William Adams https://terrierintelligence.com/professors/william-adams A pediatrician and clinical informatics researcher who develops and evaluates health information technology for children and families. His projects build electronic health record tools, patient-facing systems, and interactive voice-response interfaces aimed at improving care quality, medication safety, and health equity in urban pediatric populations. - Departments: Pediatrics, School of Medicine - Research topics: ML Theory, Healthcare, Data Science, Environment - Email: badams@bu.edu - Last verified: 2026-08-22 ### Xiaoling Zhang https://terrierintelligence.com/professors/xiaoling-zhang A bioinformatician and statistical geneticist who searches for genetic risk factors of complex diseases and the functional mechanisms behind them. Her lab integrates genome-wide DNA and RNA sequencing with statistical modeling, systems biology, and machine learning, focusing on Alzheimer's disease and its genetic overlap with cardiometabolic disorders. - Departments: Medicine, School of Medicine - Research topics: ML Theory, Healthcare, Neuroscience, Data Science - Email: zhangxl@bu.edu - Website: https://www.bu.edu/hic/profile/xiaoling-zhang/ - Last verified: 2026-08-22 ### Xin Zhang https://terrierintelligence.com/professors/xin-zhang An engineer whose research develops metamaterials and microelectromechanical systems for photonic, acoustic, and medical-imaging applications. Her Laboratory for Microsystems Technology builds structures that improve magnetic resonance imaging signal quality and enable air-permeable sound silencing, operating as a student-centered, interdisciplinary research and education program. - Departments: Mechanical Engineering, College of Engineering - Research topics: ML Theory, Healthcare, Physical Sciences - Email: xinz@bu.edu - Website: https://www.bu.edu/eng/profile/xin-zhang-ph-d/ - Last verified: 2026-08-22 ### Xuezhou Zhang https://terrierintelligence.com/professors/xuezhou-zhang A machine-learning theorist who designs interactive learning algorithms, spanning online learning, reinforcement learning, and algorithmic game theory. His work builds reinforcement-learning methods that are sample efficient and robust to noisy or adversarial feedback, with applications including language-model-assisted drug repurposing from scientific literature. - Departments: Computing & Data Sciences, Faculty of Computing & Data Sciences - Research topics: ML Theory, Data Science - Email: xuezhouz@bu.edu - Website: https://www.bu.edu/hic/profile/xuezhou-zhang/ - Last verified: 2026-08-22 ### Yuhei Miyauchi https://terrierintelligence.com/professors/yuhei-miyauchi An economist who studies how networks of production, demand, and human mobility shape economic activity within cities and across regions. He combines models from trade, urban, and macroeconomics with granular data sources, including firm-to-firm transaction records and smartphone location data, to inform policy design. - Departments: Economics, College of Arts and Sciences - Research topics: ML Theory, Data Science, Environment, Social Science - Email: miyauchi@bu.edu - Website: https://www.bu.edu/hic/profile/yuhei-miyauchi/ - Last verified: 2026-08-22 ### Yuting Zhang https://terrierintelligence.com/professors/yuting-zhang A computer systems researcher focused on mobile security and computing, and on cybersecurity education. Her Mobile Computing and Security Lab supports research and teaching in mobile platform enhancement, application analysis, and mobile sensing, and she has developed courses in mobile forensics and secure software development. - Departments: Computer Science, Metropolitan College - Research topics: ML Theory, Healthcare, Data Science, Security - Email: danazh@bu.edu - Website: https://www.bu.edu/met/profile/yuting-zhang/ - Last verified: 2026-08-22 ### Aaron Mueller https://terrierintelligence.com/professors/aaron-mueller A natural language processing researcher who studies how to understand, improve, and precisely control language models. His work applies mechanistic interpretability, causal analysis, and cognitive-science-inspired evaluation to questions of model robustness and efficiency, mentoring students who lead publications on topics such as concept unlearning and model steering. - Departments: Computer Science, College of Arts and Sciences - Research topics: ML Theory, NLP/LLMs, AI Safety - Email: amueller@bu.edu - Website: https://www.bu.edu/cs/profiles/aaron-mueller/ - Last verified: 2026-08-22 ### Aguêmon Yves Atchadé https://terrierintelligence.com/professors/yves-atchade A computational statistician developing Markov chain Monte Carlo methods and studying the theoretical properties of Bayesian procedures. His work builds statistical machinery for high-dimensional inference and applies it to environmental prediction, spanning both the asymptotic theory of sampling algorithms and their practical use on large datasets. - Departments: Mathematics & Statistics, College of Arts & Sciences, Computing & Data Sciences - Research topics: Statistics, ML Theory, Environment - Email: atchade@bu.edu - Website: http://math.bu.edu/people/atchade/ - Last verified: 2026-08-25 ### Michael Dietze https://terrierintelligence.com/professors/michael-dietze An ecological forecasting researcher whose lab builds iterative prediction systems that update continuously as new observations arrive, combining data assimilation, statistical modeling, and ecoinformatics. Applications span the terrestrial carbon cycle, vegetation phenology, and disease ecology. He chairs the Ecological Forecasting Initiative and leads the PEcAn project. - Departments: Earth & Environment, College of Arts and Sciences, Computing & Data Sciences - Research topics: Environment, Statistics, Data Science - Email: dietze@bu.edu - Website: http://people.bu.edu/dietze - Publications: https://scholar.google.com/citations?user=sYi3UiwAAAAJ&hl=en - Last verified: 2026-08-25 ### Thomas Gardos https://terrierintelligence.com/professors/thomas-gardos A computer vision and signal processing researcher who spent three decades at Intel developing deep learning applications and algorithm specifications for ultra-low-power vision chips and contributing to international video compression standards. He directs the MS in Data Science program and previously served as Intel's researcher-in-residence at the MIT Media Lab. - Departments: Computing & Data Sciences, Faculty of Computing & Data Sciences - Research topics: Computer Vision, Data Science - Email: tgardos@bu.edu - Website: https://www.bu.edu/cds-faculty/profile/thomas-gardos/ - Last verified: 2026-08-25 ### Neha Gondal https://terrierintelligence.com/professors/neha-gondal A computational sociologist who studies how interpersonal and organizational networks reproduce cultural boundaries and status distinctions. She uses exponential random graph models, agent-based simulation, and machine learning across cases ranging from Renaissance Florentine moneylending to contemporary academic and public health inequalities. - Departments: Sociology, College of Arts and Sciences, Computing & Data Sciences - Research topics: Social Science, Data Science, Healthcare - Email: gondal@bu.edu - Website: https://www.bu.edu/cds-faculty/profile/neha-gondal/ - Last verified: 2026-08-25 ### Scott Ladenheim https://terrierintelligence.com/professors/scott-ladenheim An applied mathematician working on deep learning and the iterative numerical methods that underpin large-scale scientific computing. Before joining the faculty he supported high-performance machine learning workloads at BU Research Computing Services, and his earlier research spanned applied mathematics, scientific computing, and quantum computing. - Departments: Computing & Data Sciences, Faculty of Computing & Data Sciences - Research topics: ML Theory, Data Science - Email: saladenh@bu.edu - Website: https://scottladenheim.com/ - Last verified: 2026-08-25 ### Siddharth Mishra-Sharma https://terrierintelligence.com/professors/siddharth-mishra-sharma A researcher at the intersection of machine learning and fundamental physics who develops neural methods for simulation-based inference, scalable generative modeling, and symmetry-preserving data processing. He applies these to cosmology, astrophysics, and particle physics datasets, balancing data-driven scale against physics-informed structure. - Departments: Computing & Data Sciences, Faculty of Computing & Data Sciences - Research topics: Physical Sciences, ML Theory, Generative AI/Tools - Email: smishras@bu.edu - Website: https://www.bu.edu/cds-faculty/profile/siddharth-mishra-sharma/ - Last verified: 2026-08-25 ### Ngozi Okidegbe https://terrierintelligence.com/professors/ngozi-okidegbe A legal scholar who examines how predictive technologies used in the criminal justice system affect racially marginalized communities. Her articles analyze the data underlying pretrial risk assessment tools and ask who holds decision-making power over how such algorithms are built and adopted. - Departments: Law, School of Law, Computing & Data Sciences - Research topics: Ethics, Policy, Social Science - Email: okidegbe@bu.edu - Website: https://www.bu.edu/cds-faculty/profile/okidegbe/ - Last verified: 2026-08-25 ### Krzysztof Onak https://terrierintelligence.com/professors/krzysztof-onak An algorithms researcher focused on computing over massive datasets with limited resources, covering sublinear-time algorithms, streaming and sketching, and massively parallel computation. Recent projects address fairness in clustering, graph pattern mining, and estimating properties of probability distributions. His earlier industrial work covered resource allocation and scheduling. - Departments: Computing & Data Sciences, Faculty of Computing & Data Sciences - Research topics: ML Theory, Data Science - Email: konak@bu.edu - Website: https://onak.pl/ - Last verified: 2026-08-25 ### Aldo Pacchiano https://terrierintelligence.com/professors/aldo-pacchiano A machine learning theorist who studies how algorithms learn in adaptive environments, working on reinforcement learning, online learning, bandit problems, and algorithmic fairness. He designs methods with provable efficiency and safety guarantees and applies them to biomedical research questions. - Departments: Computing & Data Sciences, Faculty of Computing & Data Sciences - Research topics: ML Theory, AI Safety, Healthcare - Email: pacchian@bu.edu - Website: https://www.aldopacchiano.ai/ - Last verified: 2026-08-25 ### Joshua Peterson https://terrierintelligence.com/professors/joshua-peterson A computational cognitive scientist who uses large behavioral datasets and machine learning to predict human judgment, covering risky decision-making, face perception, and visual object classification. Recent work tests long-standing behavioral economics theories against models fit to millions of human choices. - Departments: Computing & Data Sciences, Faculty of Computing & Data Sciences - Research topics: Social Science, ML Theory, Computer Vision - Email: joshcp@bu.edu - Website: https://datascienceofthemind.org/ - Last verified: 2026-08-25 ### Naomi Saphra https://terrierintelligence.com/professors/naomi-saphra A natural language processing researcher who studies how language models change during training, connecting optimization behavior to the generalizations models end up making. Her work draws on linguistics, deep learning theory, and interpretability, and extends to applying interpretability methods to models used for scientific discovery. - Departments: Computing & Data Sciences, Faculty of Computing & Data Sciences - Research topics: NLP/LLMs, ML Theory, AI Safety - Website: https://www.bu.edu/cds-faculty/profile/naomi-saphra/ - Last verified: 2026-08-25 ### Chris Seferlis https://terrierintelligence.com/professors/chris-seferlis An enterprise data practitioner who teaches in the online Master's in Data Science program, drawing on work in cloud architecture, data warehousing, and business intelligence. He co-authored a 2023 practical guide to Azure Cognitive Services and OpenAI aimed at technology leaders deploying AI systems. - Departments: Computing & Data Sciences, Faculty of Computing & Data Sciences - Research topics: Generative AI/Tools, Data Science - Email: seferlis@bu.edu - Website: https://seferlis.com/ - Last verified: 2026-08-25 ### Wayne Snyder https://terrierintelligence.com/professors/wayne-snyder A computer scientist whose doctoral and early research addressed computational logic and algebraic reasoning within artificial intelligence, including unification and equational theories. He now teaches in the online Master's in Data Science program and has developed courses in computational audio and natural language processing. - Departments: Computing & Data Sciences, Computer Science, Faculty of Computing & Data Sciences - Research topics: NLP/LLMs, ML Theory - Email: snyder@bu.edu - Website: https://www.bu.edu/cs/profiles/wayne-snyder/ - Last verified: 2026-08-25 ### Mayank Varia https://terrierintelligence.com/professors/mayank-varia A cryptographer who builds privacy-preserving data analysis systems and studies their social and legal dimensions. His deployments have measured gender wage gaps, tracked minority business subcontracting, and helped identify patterns across sexual assault reports. He directs the Hub for Civic Tech Impact and advises national data policy committees. - Departments: Computing & Data Sciences, Faculty of Computing & Data Sciences - Research topics: Security, Policy, Data Science - Email: varia@bu.edu - Website: https://www.mvaria.com - Publications: https://scholar.google.com/citations?hl=en&user=lneZSfIAAAAJ - Last verified: 2026-08-25 ### Lauren Wheelock https://terrierintelligence.com/professors/lauren-wheelock An optimization researcher whose work spans algorithms for matrix completion and natural language processing, machine learning for biological sequence engineering, and educational technology. She teaches mathematical foundations alongside the practice of modeling: designing, applying, and interpreting models in ambiguous settings. - Departments: Computing & Data Sciences, Faculty of Computing & Data Sciences - Research topics: ML Theory, NLP/LLMs, Education - Email: laurenbw@bu.edu - Website: https://www.bu.edu/cds-faculty/profile/lauren-wheelock/ - Publications: https://scholar.google.com/citations?user=8BOuJWsAAAAJ&hl=en - Last verified: 2026-08-25 ### Wesley Wildman https://terrierintelligence.com/professors/wesley-wildman A philosopher of religion who studies complex human social systems using computational modeling alongside the cognitive and cultural sciences. He teaches ethics of emerging technologies, working through case analyses of how data science and computational tools interact with society and public policy. - Departments: Philosophy, Theology & Ethics, School of Theology, Computing & Data Sciences - Research topics: Ethics, Humanities, Social Science - Email: wwildman@bu.edu - Website: https://wesleywildman.com/ - Last verified: 2026-08-25 ### Chris Chao Su https://terrierintelligence.com/professors/chris-chao-su A media researcher who uses computational methods to study how audiences form in a fragmented digital environment. His work analyzes mobile and social media consumption, the platform affordances that shape it, and the relationship between social media use and political behavior. - Departments: Emerging Media Studies, College of Communication, Computing & Data Sciences - Research topics: Social Science, Data Science, Policy - Email: suchao@bu.edu - Website: https://chrischaosu.com/research - Last verified: 2026-08-25 ### Najoung Kim https://terrierintelligence.com/professors/najoung-kim A computational linguist who studies how humans and machines generalize, represent meaning, and evaluate language. Her work combines computational and experimental methods to examine semantics, pragmatics, language-model behavior, and the relationship between linguistic cognition and machine representations across varied tasks and datasets. - Departments: Linguistics, Computer Science, Computing & Data Sciences - Research topics: NLP/LLMs, ML Theory, HCI - Email: najoung@bu.edu - Website: https://najoung.kim/ - Last verified: 2026-09-22 ### Chang Xiao https://terrierintelligence.com/professors/chang-xiao A human-computer interaction researcher working at the intersections of human-AI interaction, computer graphics, and augmented and virtual reality. He develops interactive systems that use generative models and visual computing to augment human creativity, communication, and physical interaction with digital content. - Departments: Computer Science - Research topics: HCI, Generative AI/Tools, Computer Vision - Email: xchang@bu.edu - Website: https://www.bu.edu/cs/profiles/chang-xiao/ - Last verified: 2026-09-22 ### John Byers https://terrierintelligence.com/professors/john-byers A computer scientist who studies algorithmic and data-analytic problems in computer networking and Internet platforms. He collaborates on interpretability research into attention in transformer models. As executive director of BU's AI Development Accelerator (AIDA), he advises the provost on AI and leads generative-AI integration across academic programs and administration. - Departments: Computer Science, Computing & Data Sciences - Research topics: Generative AI/Tools, NLP/LLMs, Data Science - Email: byers@bu.edu - Website: https://www.cs.bu.edu/fac/byers/ - Publications: https://scholar.google.com/citations?user=jIp_uw0AAAAJ&hl=en - Last verified: 2026-09-22 ### Ian Westmacott https://terrierintelligence.com/professors/ian-westmacott A software engineering leader who directs the Hariri Institute's Software & Application Innovation Lab. Before BU, he led multidisciplinary engineering teams at Symbotic, Veo Robotics, and Amazon. His work spans applied machine learning, computer vision, and robotics, and he holds more than 30 patents in video analysis and security technologies. - Departments: Hariri Institute - Research topics: Generative AI/Tools, Computer Vision, Robotics - Email: ianw@bu.edu - Website: https://www.bu.edu/hic/profile/ian-westmacott-phd/ - Accepting undergraduate researchers: yes - Last verified: 2026-09-23 ### Asad Malik https://terrierintelligence.com/professors/asad-malik A software engineer at the Software & Application Innovation Lab who serves as principal AI architect for PREAA, the lab's open-source generative-AI platform for researchers. He is also BU Spark!'s innovation engineer, co-teaches the Spark! Technology Innovation Fellowship, and leads technical workshops and consultations for students. - Departments: Hariri Institute, BU Spark! - Research topics: Generative AI/Tools, NLP/LLMs - Email: am5815@bu.edu - Accepting undergraduate researchers: yes - Last verified: 2026-09-23 ### Ziba Cranmer https://terrierintelligence.com/professors/ziba-cranmer An innovation leader and founding director of BU Spark!, the Faculty of Computing & Data Sciences' experiential lab for student technology projects. She serves on the Innovate@BU steering committee and co-teaches the Spark! Technology Innovation Fellowship. Earlier, she led a national initiative supporting public-sector innovators combating human trafficking through technology. - Departments: Computing & Data Sciences, BU Spark! - Research topics: Data Science - Email: zcranmer@bu.edu - Website: https://www.bu.edu/cds-faculty/profile/zcranmer/ - Last verified: 2026-09-23 ### James Grady https://terrierintelligence.com/professors/james-grady A designer and associate professor of graphic design in the School of Visual Arts who serves as BU Spark!'s creative director. He co-teaches the Spark! Technology Innovation Fellowship. Before BU, he co-taught information design at MIT and led design projects for clients including Google, Nike, and the World Bank. - Departments: College of Fine Arts, BU Spark! - Research topics: HCI - Email: jjgrady@bu.edu - Website: https://www.bu.edu/cfa/about/contact-directions/directory/james-grady/ - Last verified: 2026-09-23 --- ## News (40) AI-related Boston University news, newest first. ### BU ranks 25th for undergraduate AI in U.S. News 2027 rankings https://terrierintelligence.com/news/bu-us-news-ai-2027 The same release put BU at 34th overall, its best finish on the list. - Published: 2026-09-22 - Topics: Data Science, ML Theory - Original source: https://www.usnews.com/best-colleges/rankings/computer-science/artificial-intelligence ### Boston's push to lead in AI raises safety and ethics questions https://terrierintelligence.com/news/boston-push-to-lead-in-ai-raises-safety-and-ethics-questions The Daily Free Press reported on Massachusetts's effort to become a national AI leader through the state's AI Hub and startup programs such as The Open Accelerator, and on the oversight questions that growth has raised. Gov. Maura Healey called for stronger federal guardrails and independent oversight of AI. Seth Villegas, a Faculty of Computing and Data Sciences lecturer who studies technology ethics, said AI agents could pose greater risks than large language models alone. The piece shows BU students how Boston's AI policy debate is taking shape. - Published: 2026-09-22 - Topics: AI Safety, Policy, Ethics - Original source: https://dailyfreepress.com/09/22/20/220845/boston-positions-itself-as-ai-leader-amid-growing-concerns-of-safety-ethics/ ### Hariri Institute names Mona Jalal lead of Data Science Mentoring Circles https://terrierintelligence.com/news/hariri-institute-names-mona-jalal-lead-of-data-science-mentoring-circl The Hariri Institute for Computing has appointed BU alumna Mona Jalal as the new lead for its Data Science Mentoring Circles Program. Jalal brings industry experience in computer vision, synthetic data generation, and edge AI deployment to the mentoring role. - Published: 2026-09-18 - Topics: Data Science, Computer Vision, Boston University - Original source: https://www.bu.edu/hic/2026/09/18/hariri-institute-names-mona-jalal-new-lead-of-data-science-mentoring-circles-program/ ### ECE researchers receive state support for data center energy optimization project https://terrierintelligence.com/news/ece-researchers-receive-state-support-for-data-center-energy-optimizat Professors Ayşe Coskun and Emiliano Dall’Anese have received $180,000 in additional funding from the Massachusetts Clean Energy Center to expand their work on managing AI data center power consumption. The project aims to develop a multimodal framework that regulates power use under grid constraints without sacrificing performance. - Published: 2026-09-15 - Topics: Data Science, Environment, Boston University - Original source: https://www.bu.edu/eng/2026/09/15/towards-a-state-of-sustainability/ ### BU student Jeremiah Somoine wins Google Gemini hackathon prizes for empathetic AI design https://terrierintelligence.com/news/bu-student-jeremiah-somoine-wins-google-gemini-hackathon-prizes-for-em Boston University ECE senior Jeremiah Somoine earned two prizes in a Google Gemini hackathon for building user-focused generative AI applications. Somoine's projects emphasize transparency, user empathy, and trustworthiness in tools built on large language models. - Published: 2026-09-15 - Topics: Generative AI/Tools, HCI, Boston University - Original source: https://www.bu.edu/eng/2026/09/15/engineering-ai-with-sense-and-sensibility/ ### Vivek Goyal wins award for probabilistic 3D sensing research https://terrierintelligence.com/news/vivek-goyal-wins-award-for-probabilistic-3d-sensing-research Boston University Engineering Professor Vivek Goyal and his team received a Best Paper Award at the IEEE International Conference on Computational Photography. Their paper details a probabilistic modeling technique for single-photon 3D cameras that overcomes data transfer bottlenecks and light distortion. The approach enables high-flux 3D sensing without processing delays or added hardware constraints. - Published: 2026-09-10 - Topics: Computer Vision, Data Science, Boston University - Original source: https://www.bu.edu/eng/2026/09/10/cutting-to-the-chase-mathematically-speaking/ ### Deepti Ghadiyaram appointed co-director of BU's AI Research Initiative https://terrierintelligence.com/news/deepti-ghadiyaram-appointed-co-director-of-bu-s-ai-research-initiative Boston University's Hariri Institute for Computing has appointed Deepti Ghadiyaram as co-director of its Artificial Intelligence Research Initiative alongside founder Kate Saenko. Ghadiyaram, an assistant professor of computer science, specializes in safe, interpretable, and robust computer vision systems. She will help unite AI researchers across BU through research seminars and collaborative programming. - Published: 2026-09-09 - Topics: Computer Vision, AI Safety, Boston University - Original source: https://www.bu.edu/hic/2026/09/09/boston-university-appoints-deepti-ghadiyaram-as-co-director-of-air/ ### College of Engineering examines engineering requirements for production AI https://terrierintelligence.com/news/college-of-engineering-examines-engineering-requirements-for-productio An article from BU's College of Engineering outlines the transition of artificial intelligence from controlled demo prototypes to real-world deployment. It explains how software engineering discipline ensures AI models operate dependably within scalable production environments. - Published: 2026-09-04 - Topics: Generative AI/Tools, Education, Boston University - Original source: https://www.bu.edu/eng/2026/09/04/software-engineering-for-production-ready-ai-what-it-takes-to-move-beyond-prototypes/ ### BU College of Engineering highlights software engineering for AI systems https://terrierintelligence.com/news/bu-college-of-engineering-highlights-software-engineering-for-ai-syste Boston University's College of Engineering details how software engineering structures are essential for making artificial intelligence models reliable and scalable. The article discusses how combining AI pattern recognition with software workflows prepares engineers to build robust intelligent platforms and highlights master's training in AI software engineering. - Published: 2026-09-04 - Topics: Generative AI/Tools, Education, Boston University - Original source: https://www.bu.edu/eng/2026/09/04/software-engineering-for-ai-building-a-new-generation-of-intelligent-systems/ ### Azer Bestavros on why AI won't replace computing degrees https://terrierintelligence.com/news/azer-bestavros-on-why-ai-won-t-replace-computing-degrees Azer Bestavros, Associate Provost for Computing & Data Sciences at Boston University, argued that generative AI tools will not eliminate the need for computing degrees. He explained that university programs teach computational thinking, systems architecture, and critical evaluation rather than routine coding syntax. - Published: 2026-09-02 - Topics: Education, Data Science, Boston University - Original source: https://www.bu.edu/cds-faculty/2026/09/02/ai-didnt-kill-the-computing-degree/ ### BU professor Ayşe Coşkun addresses AI data center energy demands https://terrierintelligence.com/news/bu-professor-ay-e-co-kun-addresses-ai-data-center-energy-demands Boston University professor Ayşe Coşkun is serving as Chief Scientist for Emerald AI, a startup focused on optimizing data center power usage. The company's software deploys autonomous AI agents to adjust energy consumption during peak grid demand. The technology addresses public backlash and electrical grid strain caused by expanding AI infrastructure. - Published: 2026-09-01 - Topics: Policy, Environment, Boston University - Original source: https://www.bu.edu/eng/2026/09/01/on-reversing-the-data-center-backlash/ ### BU hosts Dark Energy Science Collaboration on cosmology and data science https://terrierintelligence.com/news/bu-hosts-dark-energy-science-collaboration-on-cosmology-and-data-scien Boston University hosted over 100 researchers for the Dark Energy Science Collaboration at the Center for Computing and Data Sciences. Organized by BU assistant professor Dillon Brout, the event brought together cosmologists and data scientists to analyze astronomical data from the Vera C. Rubin Observatory. - Published: 2026-08-31 - Topics: Data Science, Physical Sciences, Boston University - Original source: https://www.bu.edu/hic/2026/08/31/bu-the-universe-junior-faculty-fellow-dillon-brout-and-desc-bring-cosmology-and-data-science-together/ ### Ian Westmacott named director of BU's Software and Application Innovation Lab https://terrierintelligence.com/news/ian-westmacott-named-director-of-bu-s-software-and-application-innovat The Hariri Institute for Computing named Dr. Ian Westmacott as director of the Software and Application Innovation Lab. He will lead a team of software engineers developing custom software, computing systems, and AI infrastructure to support research across Boston University. - Published: 2026-08-28 - Topics: Generative AI/Tools, Robotics, Boston University - Original source: https://www.bu.edu/hic/2026/08/28/boston-university-welcomes-ian-westmacott-as-director-of-the-software-and-application-innovation-lab-sail-2/ ### BU researchers receive $3.37M NIH grant for molecular data tools https://terrierintelligence.com/news/bu-researchers-receive-3-37m-nih-grant-for-molecular-data-tools A Boston University team led by Assistant Professor Ruben Dries has received a $3.37 million NIH grant to develop computational tools for analyzing spatial subcellular transcriptomics datasets. The project aims to build open analytical infrastructure to help researchers process massive molecular maps without specialized computing hardware. Co-investigators include computer science and data science faculty Mark Crovella and Shariq Mohammed. - Published: 2026-08-27 - Topics: Data Science, Healthcare, Boston University - Original source: https://www.bu.edu/hic/2026/08/27/unlocking-the-data-inside-molecular-maps-ruben-dries-nih/ ### BU doctoral students win Merck In Silico Innovation Cup for AI agents https://terrierintelligence.com/news/bu-doctoral-students-win-merck-in-silico-innovation-cup-for-ai-agents Chemistry doctoral students Anand Sahu and Pridhi Balhara were part of the winning team at the 2026 Merck In Silico Innovation Cup for AI Agents. Their project developed an autonomous AI co-scientist to identify chemical solutions for semiconductor chip manufacturing. The team was selected from 41 international submissions to receive the 10,000 euro grand prize. - Published: 2026-08-26 - Topics: Generative AI/Tools, Physical Sciences, Boston University - Original source: https://www.bu.edu/hic/2026/08/26/bu-doctoral-students-anand-sahu-and-pridhi-balhara-win-2026-merck-innovation-cup-for-ai-agents/ ### BU doctoral student receives fellowship for reinforcement learning research https://terrierintelligence.com/news/bu-doctoral-student-receives-fellowship-for-reinforcement-learning-res Xinyi Hu, a PhD student in Computing & Data Sciences at Boston University, was awarded a 2026 Graduate Student Summer Fellowship from the BU Institute for Global Sustainability. Advised by Assistant Professor Aldo Pacchiano, Hu develops data-efficient reinforcement learning methods for building energy optimization. The fellowship program supports interdisciplinary graduate research addressing planetary health and sustainability challenges. - Published: 2026-08-24 - Topics: Data Science, Environment, Boston University - Original source: https://www.bu.edu/hic/2026/08/24/graduate-researchers-earn-igs-support-for-sustainability-focused-projects/ ### How do Questrom students feel about the school's expansion of AI-focused programs? https://terrierintelligence.com/news/how-do-questrom-students-feel-about-the-schools-expansion-of-ai-focused-programs The Questrom School of Business is launching a fully online Master of Science in AI in Business, with its first cohort due in Fall 2026. The two-year asynchronous program costs $25,000 in tuition and centers on AI strategy and responsible adoption for business leaders. Senior Associate Dean Paul Carlile said the program is meant to help students turn experimentation with AI into business strategy. Students interviewed by the Daily Free Press welcomed the shift, and the piece situates it alongside a Wheelock online master's on classroom AI use. - Published: 2026-08-21 - Topics: Economy, Education, Boston University - Original source: https://dailyfreepress.com/08/21/16/220312/how-do-questrom-students-feel-about-the-schools-expansion-of-ai-focused-programs/ ### Biology-informed AI model speeds antibody drug discovery https://terrierintelligence.com/news/biology-informed-ai-model-speeds-antibody-drug-discovery BU researchers showed that an AI model built around the biology of antibodies can outperform much larger general models at predicting antibody designs. The approach could shorten the early stages of drug discovery. - Published: 2026-08-13 - Topics: ML Theory, Healthcare - Original source: https://www.bu.edu/hic/2026/08/13/teaching-ai-the-biology-of-antibodies-speeds-drug-discovery/ ### BU engineers use AI to steer drug delivery in the body https://terrierintelligence.com/news/bu-engineers-use-ai-to-steer-drug-delivery-in-the-body A College of Engineering team is applying machine learning to predict how medicines reach their targets in the body. The work aims to make drug delivery more precise and reduce side effects. - Published: 2026-08-12 - Topics: Healthcare, Data Science - Original source: https://www.bu.edu/eng/2026/08/12/using-ai-to-help-medicines-get-where-they-need-to-go/ ### BU joins DOE Genesis Mission award for AI-driven plasma physics https://terrierintelligence.com/news/bu-joins-doe-genesis-mission-award-for-ai-driven-plasma-physics Boston University is a collaborating institution on a new U.S. Department of Energy Genesis Mission award that applies AI to plasma physics research. The project connects BU engineers with national-lab partners. - Published: 2026-08-11 - Topics: Physical Sciences, ML Theory - Original source: https://www.bu.edu/eng/2026/08/11/bu-partners-on-doe-genesis-mission-award-to-advance-ai-driven-plasma-physics-research/ ### Student creates AI-powered tool to help analyze classroom space usage https://terrierintelligence.com/news/student-ai-powered-tool-help-analyze-classroom-space-usage A recent Computing & Data Sciences graduate built an optimization system that assigns classes to rooms across the Charles River Campus by weighing enrollment, room capacity, and walking distance between buildings. Joey Russoniello (CDS'26) developed the tool with Lauren Wheelock through the CDS Clinics program, working with BU Information Services & Technology and support from the CDS Launchpad Fund. The tool reduced wasted seating by 92 percent and cut average walking distance from departments' home buildings by 67 percent. - Published: 2026-08-06 - Topics: Data Science, Education, Boston University - Original source: https://www.bu.edu/articles/2026/student-ai-powered-tool-help-analyze-classroom-space-usage/ ### NSF awards Boston University $20 million to help create national "cloud lab" network https://terrierintelligence.com/news/nsf-awards-20-million-establish-national-cloud-lab-network A $20 million NSF award will expand BU's DAMP Lab cloud lab and link it to a national network of 20 AI-driven research facilities, aiming to democratize access to advanced biotechnology capabilities for researchers nationwide. - Published: 2026-07-23 - Topics: Robotics, Boston University - Original source: https://www.bu.edu/articles/2026/nsf-awards-20-million-establish-national-cloud-lab-network/ ### BU engineers train an adaptable AI model to read brain MRI scans https://terrierintelligence.com/news/bu-engineers-train-adaptable-ai-model-to-read-brain-mri-scans A College of Engineering team in Xin Zhang's Laboratory for Microsystems Technology trained a transformer-based foundation model on general patterns in brain MRI scans, so it can be adapted to specific diagnostic tasks with only a few labeled examples. The approach targets a common hospital constraint: plenty of imaging data but few expert-labeled cases. Radiologist Chad Farris of the Chobanian & Avedisian School of Medicine said faster reads could help flag acute conditions such as stroke. The Brink featured the work again in its September 18 research roundup. - Published: 2026-07-21 - Topics: Computer Vision, Healthcare - Original source: https://www.bu.edu/eng/2026/07/21/can-we-train-ai-to-read-an-mri/ ### Three New CAS Master's Programs Will Take Students to the Cutting Edge https://terrierintelligence.com/news/cas-new-masters-programs-2026 BU's College of Arts & Sciences announced three new master's programs aimed at emerging technical fields, including computing and data-intensive work. - Published: 2026-07-09 - Topics: Education, Data Science - Original source: https://www.bu.edu/articles/2026/three-new-college-of-arts-and-sciences-masters-programs/ ### Fictional Bibliographies: ENG Tool Catches Hallucinated Citations https://terrierintelligence.com/news/stringhini-hallucinated-citations-tool ECE professor Gianluca Stringhini released an open-source tool that helps peer reviewers detect AI-hallucinated citations in academic manuscripts. - Published: 2026-06-17 - Topics: NLP/LLMs, Ethics - Original source: https://www.bu.edu/eng/2026/06/17/fictional-bibliographies/ ### ECE Researchers Sweep Hariri Institute's 2026 Awards https://terrierintelligence.com/news/ece-hariri-2026-awards ECE faculty and students were recognized across every category of the Hariri Institute's 2026 cohort, including new Junior Faculty Fellow Wei-Lun (Harry) Chao and a neuro-AI Focused Research Program on striatal learning. - Published: 2026-06-16 - Topics: ML Theory, Healthcare - Original source: https://www.bu.edu/eng/2026/06/16/cultivating-computational-excellence/ ### CDS Announces 2026 Faculty, Staff, and Student Awards https://terrierintelligence.com/news/cds-2026-community-awards CDS closed the 2025-26 academic year by recognizing students, faculty, and staff for research and community impact. - Published: 2026-06-11 - Topics: Data Science - Original source: https://www.bu.edu/cds-faculty/2026/06/11/2026-faculty-staff-student-awards/ ### BU Joins NSF Institute Pushing Frontiers of Physics and AI https://terrierintelligence.com/news/bu-joins-nsf-iaifi BU became a core member of the NSF AI Institute for Artificial Intelligence and Fundamental Interactions (IAIFI) alongside MIT, Harvard, Northeastern, and Tufts. CDS Assistant Professor Siddharth Mishra-Sharma leads BU's participation. - Published: 2026-06-04 - Topics: ML Theory - Original source: https://www.bu.edu/articles/2026/bu-joins-national-science-foundation-ai-institute/ ### Center for Health Data Science launches DataHub for AI-driven research https://terrierintelligence.com/news/health-data-science-datahub BU's School of Public Health launched DataHub, a Center for Health Data Science initiative to help researchers discover, access, and responsibly use health data for AI-driven, cross-disciplinary work. - Published: 2026-06-02 - Topics: Healthcare, Data Science - Original source: https://www.bu.edu/sph/news/articles/2026/center-for-health-data-science-launches-datahub-to-advance-ai-driven-and-convergent-research/ ### CDS and Bioinformatics Faculty and Students Recognized for Innovation https://terrierintelligence.com/news/hariri-2026-fellowship-awardees The Hariri Institute announced its 2026 fellowship and research program awardees, with several CDS and Bioinformatics faculty and students among them. - Published: 2026-05-28 - Topics: Data Science, Healthcare - Original source: https://www.bu.edu/cds-faculty/2026/05/28/hariri-awards/ ### BU-Based Outbreak Tracker BEACON Monitors World's Most Dangerous Infectious Diseases https://terrierintelligence.com/news/beacon-outbreak-tracker BEACON, run out of BU's Center for Emerging Infectious Diseases, uses AI to scan large volumes of data for early signals of outbreaks like measles, cholera, and mpox before they surface through standard public health channels. - Published: 2026-05-18 - Topics: Healthcare, Data Science - Original source: https://www.bu.edu/articles/2026/measles-cholera-outbreak-tracker-monitors-infectious-diseases/ ### CDS's Xuezhou Zhang Secures NIH Funding for AI-Driven Drug Repurposing https://terrierintelligence.com/news/zhang-nih-ai-drug-repurposing CDS Assistant Professor Xuezhou "Jack" Zhang received NIH funding for a collaboration applying AI to drug repurposing. - Published: 2026-05-06 - Topics: Healthcare - Original source: https://www.bu.edu/cds-faculty/2026/05/06/zhang-nih-ai-drug-repurposing/ ### Studying How Online Images Feed Polarization Wins BU Scholar Carnegie Fellowship https://terrierintelligence.com/news/lokmanoglu-carnegie-fellowship COM professor Ayse Lokmanoglu won an Andrew Carnegie Fellowship for computational work on how online imagery drives political polarization. - Published: 2026-05-05 - Topics: Policy, Computer Vision - Original source: https://www.bu.edu/articles/2026/polarization-study-wins-andrew-carnegie-fellowship/ ### Storms, Waves, and a Century of Simulated Weather https://terrierintelligence.com/news/ace2-climate-emulator CDS researcher Mu-Ting Chien is using the ACE2 deep learning climate emulator to study weather and climate variability at century scale. - Published: 2026-04-27 - Topics: Environment - Original source: https://www.bu.edu/cds-faculty/2026/04/27/mu-ting-chien-ace2-climate-emulator/ ### Can AI help predict the Earth's climate decades from now? https://terrierintelligence.com/news/can-ai-help-predict-climate-decades-from-now BU's Elizabeth Barnes combines AI with Earth sciences to improve climate and weather predictions across timescales from days to decades, aiming to accelerate Earth system modeling while preserving scientific rigor and uncertainty quantification. - Published: 2026-03-04 - Topics: Environment, Boston University - Original source: https://www.bu.edu/articles/2026/can-ai-help-predict-climate-decades-from-now/ ### CDS faculty fellow Brian DePasquale wins Sloan Research Fellowship https://terrierintelligence.com/news/brian-depasquale-sloan-fellowship Brian DePasquale, a CDS faculty fellow and assistant professor of biomedical engineering, received a 2026 Sloan Research Fellowship. The Alfred P. Sloan Foundation named 126 fellows from more than 1,000 nominees, and each fellow received $75,000 over two years. DePasquale builds mathematical models of how neurons produce movements, decisions, and perceptions. He plans to use the award to develop AI and mathematical models of how chemicals produce the perception of smell. Biomedical engineering vice chair Mary Dunlop said the work could improve devices that turn brain signals into commands for robotic limbs and computers. - Published: 2026-02-17 - Topics: ML Theory, Neuroscience, Healthcare - Original source: https://www.bu.edu/cds-faculty/2026/02/17/brian-depasquale-sloan-fellowship/ ### Debbie Cheng appointed AIDA's Director of Strategy and Partnerships https://terrierintelligence.com/news/aida-director-strategy-partnerships The AI Development Accelerator named Hariri Institute faculty affiliate Debbie Cheng as Director of Strategy and Partnerships, following an AIDA symposium on real-world generative-AI use in research and education. - Published: 2026-02-11 - Topics: Boston University - Original source: https://www.bu.edu/hic/2026/02/11/debbie-cheng-appointed-aidas-director-of-strategy-and-partnerships/ ### Joshua Peterson leads DARPA-funded study on AI trust https://terrierintelligence.com/news/joshua-peterson-study-ai-trust Joshua Peterson, an assistant professor in the Faculty of Computing & Data Sciences, secured funding from the Defense Advanced Research Projects Agency (DARPA) for an 18-month project called "Predicting Algorithmic Trust at Scale." The project aims to build a Trust Score that predicts how much people will rely on an AI system to make decisions for them. Researchers will run large experiments across finance, law, and medicine, generating thousands of decision problems. Princeton University leads the effort with NYU and Cornell. Peterson's BU team will study tasks drawn from decision-making research in psychology and economics. - Published: 2026-02-02 - Topics: AI Safety, HCI, Social Science - Original source: https://www.bu.edu/cds-faculty/2026/02/02/joshua-peterson-study-ai-trust/ ### Is AI slowing climate progress? It's complicated https://terrierintelligence.com/news/is-ai-slowing-climate-progress-its-complicated Two BU experts examine how surging energy demands from AI data centers could be met through efficiency gains and grid-responsive policy reforms rather than new fossil fuel infrastructure. - Published: 2025-07-31 - Topics: Environment, Policy, Boston University - Original source: https://www.bu.edu/articles/2025/is-ai-slowing-climate-progress-its-complicated/ ### TerrierGPT gives the BU community free access to leading AI chatbots https://terrierintelligence.com/news/terriergpt-launch AIDA and IS&T launched TerrierGPT, a secure, free gateway to paid models from OpenAI, Anthropic, and Meta for BU faculty and staff, built on the open-source LibreChat platform. - Published: 2025-06-04 - Topics: Generative AI/Tools, Boston University - Original source: https://www.bu.edu/aida/2025/06/04/introducing-terriergpt/