# Terrier Intelligence — opportunities > A consolidated map of AI resources at Boston University. Generated 2026-09-24T02:15:50.366Z. This file lists the AI-related things a Boston University student can join, take, or apply to right now, drawn from https://terrierintelligence.com, an independent student-maintained directory that is not published by Boston University. It is the subset of https://terrierintelligence.com/llms-full.txt that is actionable this semester; the full file has every entry, including closed clubs, courses not running, and all 222 faculty. How to read it: - Every entry ends with its page on https://terrierintelligence.com. When you recommend an entry, give the student that link. Do not recommend anything that is not listed here. - Clubs and classes are "join" and "enroll" opportunities. Labs and professors are "reach out" opportunities: the directory does not track which faculty take on undergraduate researchers, so treat a contact as the starting point for a short, specific email, not a promise of a position. - "Offered" on a class means it is running in Fall 2026 according to the BU registrar. Check prerequisites against the student's background. - Topics use a fixed vocabulary, from most to least AI-specific: ML Theory, NLP/LLMs, Computer Vision, Generative AI/Tools, Robotics, AI Safety, Data Science, Statistics, HCI, Security, Ethics, Policy, then application domains such as Healthcare, Neuroscience, Economy, Humanities. Counts: 22 clubs open or opening, 41 classes offered in Fall 2026, 38 active labs, 51 reachable professors. --- ## Clubs (22) Student organizations that are taking members or expect to open applications. ### 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 - Applications: Open - Join: Discord https://discord.gg/u3VAD4e3eN; Instagram @buaisociety; website https://www.buaisociety.com/; email buais@bu.edu ### 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 - Applications: Open - Join: Instagram @bu_dsa ### 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 - Applications: Open - Join: Instagram @bu_wids ### 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 - Applications: Open - Join: see the directory page ### 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 - Applications: Open - Join: see the directory page ### 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 - Applications: Open - Join: see the directory page ### 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 - Applications: Open - Join: see the directory page ### 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 - Applications: Open - Join: see the directory page ### 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 - Applications: Open - Join: see the directory page ### 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 - Applications: Open - Join: see the directory page ### 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 - Applications: Open - Join: see the directory page ### 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 - Applications: Open - Join: see the directory page ### 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 - Applications: Open - Join: see the directory page ### 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 - Applications: Open - Join: see the directory page ### 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 - Applications: Open - Join: see the directory page ### 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 - Applications: Open - Join: see the directory page ### 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 - Applications: Open - Join: see the directory page ### 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 - Applications: Apply Later - Join: email msachdev@bu.edu ### 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 - Applications: Apply Later - Faculty advisor: Kenn Sebesta - Join: website https://www.bu.edu/eng/student-engagement-careers/student-engagement/student-clubs-organizations/bu-robotics-club/ ### 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 - Applications: Apply Later - Join: Instagram @bu_sportsanalytics; email busportsanalytics@gmail.com ### 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 - Applications: Apply Later - Join: Instagram @ktpbostonu; website https://www.ktp-bostonu.com/; email rcheng86@bu.edu ### 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 - Applications: Apply Later - Join: email devb@bu.edu --- ## Classes (41) Courses running in Fall 2026. Level is one of intro, intermediate, advanced, grad. ### 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. - Department: CAS - Level: intro - Topics: Ethics - Credits: 4 - Enroll: register for Fall 2026 ### 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. - Department: CAS - Level: grad - Topics: Data Science - Credits: 4 - Prerequisites: CS 108/111; CS 132 or MA 242/442 - Enroll: register for Fall 2026 ### 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. - Department: CAS - Level: grad - Topics: ML Theory, Data Science - Credits: 4 - Prerequisites: CS 111/112; CS 132 or MA 242; CS 237 or MA 581 - Enroll: register for Fall 2026 ### 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. - Department: CAS - Level: grad - Topics: ML Theory - Credits: 4 - Prerequisites: CS 365 - Enroll: register for Fall 2026 ### 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. - Department: CAS - Level: grad - Topics: ML Theory, Data Science - Credits: 4 - Prerequisites: CS 505 or CS 542 or CS 585 - Cross-listed as: DS 549 - Enroll: register for Fall 2026 ### 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. - Department: CAS - Level: grad - Topics: Computer Vision, Robotics - Credits: 4 - Prerequisites: CS 330; CS 132 or MA 242 - Enroll: register for Fall 2026 ### 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. - Department: MET - Level: grad - Topics: ML Theory, Generative AI/Tools - Credits: 4 - Prerequisites: MET CS 521 & one of 577/622/673/682 - Enroll: register for Fall 2026 ### 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. - Department: MET - Level: grad - Topics: ML Theory, NLP/LLMs - Credits: 4 - Prerequisites: MET CS 526 or MET CS 673 - Enroll: register for Fall 2026 ### 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. - Department: ENG - Level: advanced - Topics: ML Theory - Credits: 4 - Enroll: register for Fall 2026 ### 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. - Department: ENG - Level: grad - Topics: ML Theory, Statistics - Credits: 4 - Enroll: register for Fall 2026 ### 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. - Department: ENG - Level: grad - Topics: ML Theory, Computer Vision, Generative AI/Tools - Credits: 4 - Cross-listed as: CS 523 - Enroll: register for Fall 2026 ### 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. - Department: CS - Level: intermediate - Topics: Data Science, Statistics - Credits: 4 - Prerequisites: CS 112 & 131 & 132 & 237 - Taught by: Charalampos (Babis) Tsourakakis - Enroll: register for Fall 2026 ### 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. - Department: CS - Level: advanced - Topics: Computer Vision, Robotics - Credits: 4 - Prerequisites: CS 112 & CS 132 - Enroll: register for Fall 2026 ### 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. - Department: CDS - Level: intermediate - Topics: Data Science - Credits: 4 - Prerequisites: DS 121 & DS 210 - Taught by: Krzysztof Onak - Enroll: register for Fall 2026 ### 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. - Department: CDS - Level: intermediate - Topics: ML Theory, Data Science - Credits: 4 - Prerequisites: DS 122 & DS 320 - Taught by: Kevin Gold - Enroll: register for Fall 2026 ### 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. - Department: CS - Level: grad - Topics: ML Theory - Credits: 4 - Prerequisites: MA 123 & 124; CS 132 - Enroll: register for Fall 2026 ### 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. - Department: ENG - Level: grad - Topics: ML Theory, Robotics, Computer Vision - Credits: 4 - Prerequisites: MA 225, EK 103, EK 381, EK 128, EC 414 - Enroll: register for Fall 2026 ### 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. - Department: ENG - Level: grad - Topics: ML Theory - Credits: 4 - Prerequisites: EK 103 or MA 142 - Enroll: register for Fall 2026 ### 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. - Department: ENG - Level: grad - Topics: Robotics - Credits: 4 - Prerequisites: MA 226, EK 103, EK 121/125 - Taught by: Roberto Tron - Enroll: register for Fall 2026 ### 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. - Department: Math - Level: grad - Topics: ML Theory - Credits: 4 - Prerequisites: MA 225 & MA 242 - Enroll: register for Fall 2026 ### 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. - Department: CDS - Level: intermediate - Topics: Ethics, Policy - Credits: 4 - Enroll: register for Fall 2026 ### 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. - Department: CDS - Level: grad - Topics: ML Theory - Credits: 4 - Prerequisites: DS 122; MA 581/CS 237/EK 381 - Enroll: register for Fall 2026 ### 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. - Department: CAS - Level: intermediate - Topics: Generative AI/Tools, Ethics, HCI - Credits: 4 - Prerequisites: First-Year Writing Seminar and WR 151/152/153 - Taught by: Pary Fassihi , Chris McVey - Enroll: register for Fall 2026; bulletin https://www.bu.edu/academics/cas/courses/cas-wr-250/ ### 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. - Department: ENG - Level: grad - Topics: Robotics, Computer Vision, ML Theory - Credits: 4 - Prerequisites: Graduate standing - Enroll: register for Fall 2026; bulletin https://www.bu.edu/academics/eng/programs/mechanical-engineering/ms-in-robotics-autonomous-systems/ ### 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. - Department: ENG - Level: advanced - Topics: Robotics, Computer Vision, ML Theory - Credits: 4 - Prerequisites: ME 302, EC 327, EC 401, or BE 403 - Taught by: Kenn Sebesta - Enroll: register for Fall 2026; bulletin https://www.bu.edu/academics/eng/courses/eng-me-416/ ### 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. - Department: ENG - Level: grad - Topics: Robotics, Healthcare, Computer Vision - Credits: 4 - Prerequisites: See bulletin - Taught by: Sheila Russo - Enroll: register for Fall 2026; bulletin https://www.bu.edu/eng/files/2025/08/Robotics-Autonomous-Systems-Spring-2026-Grad-Courses-One-Pager-Fall-2025.pdf ### 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. - Department: MET - Level: grad - Topics: Generative AI/Tools, NLP/LLMs, Data Science - Credits: 4 - Prerequisites: Corequisite MET AD 100 Lab - Enroll: register for Fall 2026; bulletin https://www.bu.edu/academics/met/courses/met-ad-698/ ### 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. - Department: MET - Level: grad - Topics: ML Theory, Robotics, AI Safety - Credits: 4 - Prerequisites: MET CS 767 or consent - Taught by: Reza Rawassizadeh - Enroll: register for Fall 2026; bulletin https://www.bu.edu/met/degrees-certificates/ms-applied-data-analytics-ai-machine-learning/ ### 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. - Department: MET - Level: grad - Topics: Generative AI/Tools, NLP/LLMs, Computer Vision - Credits: 4 - Prerequisites: MET CS 577 plus Python, ML math, and neural networks - Taught by: Reza Rawassizadeh - Enroll: register for Fall 2026; bulletin https://www.bu.edu/academics/met/courses/met-cs-788/ ### 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. - Department: Questrom - Level: advanced - Topics: ML Theory, Data Science - Credits: 4 - Prerequisites: CAS CS 108/111, CDS DS 110, or QST BA 222 - Cross-listed as: BA 476 - Taught by: Georgios Zervas , Gerdus Benade - Enroll: register for Fall 2026; bulletin https://www.bu.edu/academics/questrom/courses/qst-ba-576/ ### 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. - Department: Questrom - Level: grad - Topics: ML Theory, Data Science - Credits: 3 - Prerequisites: QST BA 600, 602, 780 - Enroll: register for Fall 2026; bulletin https://www.bu.edu/academics/questrom/courses/qst-ba-810/ ### 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. - Department: Questrom - Level: grad - Topics: Data Science, Generative AI/Tools - Credits: 3 - Prerequisites: QST BA 600, 602, 780, 810, 820 - Enroll: register for Fall 2026; bulletin https://www.bu.edu/academics/questrom/courses/qst-ba-882/ ### 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. - Department: Questrom - Level: grad - Topics: Generative AI/Tools, NLP/LLMs, Ethics - Credits: 3 - Prerequisites: MSDT students only - Enroll: register for Fall 2026; bulletin https://www.bu.edu/academics/questrom/courses/qst-is-883/ ### 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. - Department: Questrom - Level: grad - Topics: ML Theory, Statistics - Credits: 3 - Prerequisites: MSMFT restrictions may apply - Enroll: register for Fall 2026; bulletin https://www.bu.edu/academics/questrom/courses/qst-mf-850/ ### 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. - Department: Wheelock - Level: grad - Topics: Education, Generative AI/Tools, Ethics - Credits: 4 - Prerequisites: Admission to or approval from the AI & Education program - Enroll: register for Fall 2026; bulletin https://www.bu.edu/academics/wheelock/programs/artificial-intelligence/edm-in-ai-education/ ### 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. - Department: Wheelock - Level: grad - Topics: Education, Generative AI/Tools, Ethics - Credits: 4 - Prerequisites: Admission to or approval from the AI & Education program - Enroll: register for Fall 2026; bulletin https://www.bu.edu/academics/wheelock/programs/artificial-intelligence/edm-in-ai-education/ ### 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. - Department: CAS - Level: intro - Topics: Generative AI/Tools, Education - Credits: 4 - Enroll: register for Fall 2026; bulletin https://www.bu.edu/academics/cas/courses/cas-cs-103/ ### 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. - Department: CAS - Level: intermediate - Topics: Generative AI/Tools, Education - Credits: 4 - Prerequisites: CS 111, CS 112 - Enroll: register for Fall 2026 ### 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. - Department: CAS - Level: grad - Topics: Generative AI/Tools, NLP/LLMs, AI Safety - Credits: 4 - Prerequisites: One of CS 440, CS 505, CS 523, CS 541, or CS 542 with a B+ or higher, or instructor permission - Enroll: register for Fall 2026; bulletin https://www.bu.edu/academics/cas/courses/cas-cs-598/ ### 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. - Department: CAS - Level: intermediate - Topics: Generative AI/Tools, Education, Humanities - Credits: 4 - Enroll: register for Fall 2026; bulletin https://www.bu.edu/academics/cas/courses/cas-hi-393/ ### 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. - Department: BU Spark! - Level: advanced - Topics: Generative AI/Tools - 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. - Cross-listed as: CFA AR 675 - Taught by: Asad Malik , Ziba Cranmer , James Grady - Enroll: register for Fall 2026 --- ## Labs (38) Active 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 - Reach out: email Daniel Munro or Seth Villegas ; read https://www.bu.edu/philo/community/the-humanities-and-artificial-intelligence-lab/ first ### 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 - Reach out: email Kate Saenko or Deepti Ghadiyaram ; read https://www.bu.edu/hic/centers-and-initiatives-2/air/ first ### 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 - Reach out: email Naomi Caselli or Michael Chang or Elena Forzani or Jennifer Green or Eshed Ohn-Bar or Ola Ozernov-Palchik ### 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 - Reach out: email Ola Ozernov-Palchik ; read https://www.bu.edu/hic/centers-initiatives-labs/eval/ first ### 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 - Reach out: no named lead in the directory; start from https://sites.bu.edu/aiem/ ### 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 - Reach out: email Kayhan Batmanghelich ; read https://www.batman-lab.com/ first ### 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 - Reach out: no named lead in the directory; start from https://www.bu.edu/bmerc/ ### 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 - Reach out: email Simon Kasif ; read https://sites.bu.edu/phenogeno/ first ### 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 - Reach out: email Dokyun Lee ; read https://www.leedokyun.com/bitlab.html first ### 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 - Reach out: email Kate Saenko ; read https://ai.bu.edu/ first ### 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 - Reach out: email Venkatesh Saligrama ; read https://sites.bu.edu/data/ first ### 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 - Reach out: no named lead in the directory; start from https://www.bu.edu/cs/ivc/ ### 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 - Reach out: email Emily Whiting ; read https://shape.bu.edu/ first ### 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 - Reach out: email Janusz Konrad ; read https://vip.bu.edu/ first ### 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 - Reach out: email John Byers ; read https://www.bu.edu/aida/ first ### 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 - Reach out: email Brian Cleary ; read https://www.algobiolab.com first ### 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 - Reach out: email Brian DePasquale ; read https://depasquale-lab.github.io/ first ### 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 - Reach out: email Elizabeth Barnes ; read https://barnes-research.com/ first ### 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 - Reach out: no named lead in the directory; start from https://sites.bu.edu/robotics/ ### 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 - Reach out: no named lead in the directory; start from https://www.bu.edu/eng/2018/03/12/center-for-autonomous-and-robotics-systems/ ### 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 - Reach out: email Lei Tian ; read https://sites.bu.edu/tianlab/ first ### 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 - Reach out: email Wenchao Li ; read https://sites.bu.edu/depend/ first ### 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 - Reach out: email Dokyun Lee ; read https://www.bu.edu/dbi/ first ### 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 - Reach out: email Emma Wiles ; read https://www.emmawiles.com/ first ### 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 - Reach out: email Vijaya Kolachalama ; read https://vkola-lab.github.io/ first ### 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 - Reach out: email Gianluca Stringhini ; read https://seclab.bu.edu/ first ### 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 - Reach out: no named lead in the directory; start from https://www.bu.edu/cs/research-groups/ml/ ### 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 - Reach out: email Sheila Russo ; read https://sites.bu.edu/mrl/ first ### 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 - Reach out: email Alyssa Pierson ; read https://sites.bu.edu/pierson/ first ### 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 - Reach out: email Ioannis Paschalidis ; read https://sites.bu.edu/paschalidis/ first ### 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 - Reach out: email Archana Venkataraman ; read https://www.nsa-lab.org/ first ### 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 - Reach out: email Ayse Coskun ; read https://www.bu.edu/peaclab/ first ### 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 - Reach out: email Kenn Sebesta ; read https://www.bu.edu/eng/academics/departments-and-divisions/mechanical-engineering/rastic/ first ### 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 - Reach out: no named lead in the directory; start from https://www.bu.edu/cs/research-groups/vg/ ### 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 - Reach out: email Eshed Ohn-Bar ; read https://eshed1.github.io/ first ### 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 - Reach out: email Najoung Kim ; read https://najoung.kim/tinlab/ first ### 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 - Reach out: email Ian Westmacott ; read https://sail.codes first ### 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 - Reach out: email Ioannis Paschalidis ; read https://www.bu.edu/hic/ first --- ## Professors (51) Faculty who lead or belong to a lab above, or teach a class above. Bios are shortened; the directory page has the full one. ### 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 multimoda… - Departments: Computer Science - Research topics: Computer Vision, ML Theory, NLP/LLMs - Labs: AI Research Initiative (AIR), Computer Vision and Learning Group - Website: https://ai.bu.edu/ - Reach out: email saenko@bu.edu ### 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 advise… - Departments: Electrical & Computer Engineering, Systems Engineering - Research topics: ML Theory, Computer Vision, Statistics - Labs: AI Research Initiative (AIR), Data Science & Machine Learning Lab (Saligrama Lab) - Website: https://sites.bu.edu/data/ - Reach out: email srv@bu.edu ### 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… - Departments: ENG (ECE, SE), Computer Science, CDS - Research topics: ML Theory - Labs: AI Research Initiative (AIR) - Website: https://www.bu.edu/cs/profiles/brian-kulis/ - Reach out: email bkulis@bu.edu ### 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 learn… - Departments: Computer Science - Research topics: Computer Vision, NLP/LLMs - Labs: AI Research Initiative (AIR) - Website: https://www.bu.edu/cs/profiles/bplum/ - Reach out: email bplum@bu.edu ### 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… - Departments: Computer Science (affil. ECE, CDS) - Research topics: Computer Vision, Generative AI/Tools, AI Safety - Labs: AI Research Initiative (AIR) - Website: https://deeptigp.github.io/ - Reach out: email dghadiya@bu.edu ### 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-… - Departments: Computer Science - Research topics: Computer Vision, ML Theory - Labs: AI Research Initiative (AIR) - Website: https://www.bu.edu/cs/profiles/boqing-gong/ - Reach out: email bgong@bu.edu ### 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 syst… - Departments: Computer Science - Research topics: Computer Vision - Labs: AI Research Initiative (AIR), Image and Video Computing (IVC) - Website: https://www.bu.edu/cs/profiles/stan-sclaroff/ - Reach out: email sclaroff@bu.edu ### 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 techniq… - Departments: Computer Science - Research topics: NLP/LLMs, ML Theory - Labs: AI Research Initiative (AIR) - Website: https://www.bu.edu/cs/profiles/derry-wijaya/ - Reach out: email wijaya@bu.edu ### 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… - Departments: Electrical & Computer Engineering - Research topics: Healthcare, ML Theory, Computer Vision - Labs: Batman Lab - Website: https://www.batman-lab.com/ - Reach out: email batman@bu.edu ### 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 me… - Departments: Biomedical Engineering / Bioinformatics, Computer Science - Research topics: Healthcare, ML Theory, Data Science - Labs: Bridges from AI to Understanding and Reprograming Biology (2AI2BIO) - Website: https://sites.bu.edu/phenogeno/ - Reach out: email kasif@bu.edu ### 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… - Departments: Questrom (Information Systems), CDS - Research topics: Data Science, NLP/LLMs, Generative AI/Tools - Labs: Business Insights through Text (BIT) Lab, Digital Business Institute Generative AI Lab - Website: https://www.leedokyun.com/ - Reach out: email dokyun@bu.edu ### 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 mechani… - Departments: Computer Science - Research topics: HCI - Labs: Shape Lab - Website: https://shape.bu.edu/ - Reach out: email whiting@bu.edu ### 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 bu… - Departments: Electrical & Computer Engineering - Research topics: Computer Vision - Labs: Visual Information Processing (VIP) Lab - Website: https://vip.bu.edu/ - Reach out: email jkonrad@bu.edu ### 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… - Departments: Electrical & Computer Engineering - Research topics: Computer Vision, ML Theory, Statistics - Labs: Visual Information Processing (VIP) Lab - Website: https://vip.bu.edu/ - Reach out: email pi@bu.edu ### 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 langua… - Departments: Philosophy (CAS) - Research topics: Ethics, Policy - Labs: Humanities & AI Lab (HAIL) - Reach out: email dmunro@bu.edu ### 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… - Departments: Philosophy (CAS) - Research topics: Ethics, Policy - Labs: Humanities & AI Lab (HAIL) - Website: https://www.bu.edu/cds-faculty/profile/seth-villegas/ - Reach out: email sethvill@bu.edu ### 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… - Departments: Wheelock College of Education & Human Development - Research topics: Education, NLP/LLMs - Labs: AI and Education Initiative - Website: https://www.bu.edu/hic/profile/naomi-caselli/ - Reach out: email nkc@bu.edu ### 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 C… - Departments: Wheelock College of Education & Human Development - Research topics: Education - Labs: AI and Education Initiative - Website: https://www.bu.edu/cds-faculty/profile/michael-chang/ - Reach out: email machang@bu.edu ### 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… - Departments: Wheelock College of Education & Human Development - Research topics: Education - Labs: AI and Education Initiative - Reach out: email eforzani@bu.edu ### 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 prevent… - Departments: Wheelock College of Education & Human Development - Research topics: Education - Labs: AI and Education Initiative - Website: https://www.bu.edu/hic/profile/jennifer-green/ - Reach out: email jggreen@bu.edu ### 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 v… - Departments: Electrical & Computer Engineering - Research topics: Computer Vision, Robotics - Labs: AI and Education Initiative, Human-to-Everything (H2X) Lab - Website: https://www.bu.edu/hic/profile/eshed-ohn-bar/ - Reach out: email eohnbar@bu.edu ### 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-bas… - Departments: Wheelock College of Education & Human Development, Hariri Institute - Research topics: Education, Healthcare - Labs: AI and Education Initiative, Evidence-Based AI in Learning (EVAL) Industry Collaborative - Website: https://www.bu.edu/hic/profile/ola-ozernov-palchik/ - Reach out: email oozernov@bu.edu ### 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, a… - Departments: Computer Science - Research topics: Data Science, ML Theory - Website: https://tsourakakis.com/ - Reach out: email ctsourak@bu.edu ### 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 Epso… - Departments: Computing & Data Sciences - Research topics: ML Theory, Education - Website: https://www.bu.edu/cds-faculty/profile/klgold/ - Reach out: email klgold@bu.edu ### 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 d… - Departments: Mechanical Engineering - Research topics: Robotics - Website: https://www.bu.edu/eng/profile/roberto-tron/ - Reach out: email tron@bu.edu ### 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 e… - Departments: Mechanical Engineering, College of Engineering - Research topics: Robotics - Labs: Multi-Robot Systems Lab - Website: https://www.bu.edu/hic/profile/alyssa-pierson/ - Reach out: email pierson@bu.edu ### 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 charact… - Departments: Electrical and Computer Engineering, College of Engineering - Research topics: ML Theory, NLP/LLMs, Healthcare, Neuroscience - Labs: Neural Systems Analysis Laboratory (NSA Lab) - Website: https://www.bu.edu/eng/profile/archana-venkataraman-ph-d/ - Reach out: email archanav@bu.edu ### 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… - Departments: Electrical and Computer Engineering, College of Engineering - Research topics: ML Theory, Robotics, Physical Sciences, Environment - Labs: Performance and Energy-Aware Computing Laboratory (PeacLab) - Website: https://www.bu.edu/hic/profile/ayse-coskun/ - Reach out: email acoskun@bu.edu ### 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 vir… - Departments: Biomedical Engineering, Biology - Research topics: ML Theory, Healthcare - Labs: Algorithmic Lens on Experimental Biology Laboratory - Website: https://www.bu.edu/cds-faculty/profile/bcleary/ - Reach out: email bcleary@bu.edu ### 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… - Departments: Biomedical Engineering, College of Engineering - Research topics: ML Theory, Neuroscience, Data Science - Labs: Artificial and Biological Intelligence Lab - Website: https://www.bu.edu/eng/profile/brian-depasquale-ph-d/ - Reach out: email bddepasq@bu.edu ### 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 e… - Departments: Writing Program - Research topics: Generative AI/Tools, Humanities, Education - Website: https://www.bu.edu/writingprogram/profile/christopher-mcvey/ - Reach out: email cmcvey@bu.edu ### 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, pred… - Departments: Earth & Environment, Computing & Data Sciences, College of Arts & Sciences, CDS - Research topics: Environment - Labs: Barnes Group - Website: https://www.bu.edu/earth/profiles/elizabeth-barnes/ - Reach out: email eabarnes@bu.edu ### 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… - Departments: Information Systems, Questrom School of Business - Research topics: HCI - Labs: Human-AI Interaction in Recruiting & Employment (HIRE) Lab - Website: https://www.bu.edu/questrom/profiles/emma-wiles/ - Reach out: email ewiles@bu.edu ### 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, an… - Departments: Marketing, Questrom School of Business - Research topics: ML Theory, Data Science - Website: https://www.bu.edu/questrom/profiles/georgios-zervas/ - Reach out: email zg@bu.edu ### 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, participa… - Departments: Information Systems, Questrom School of Business - Research topics: ML Theory, Data Science, Social Science, Policy - Website: https://www.bu.edu/questrom/profiles/gerdus-benade/ - Reach out: email benade@bu.edu ### 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 harassmen… - Departments: Electrical and Computer Engineering, College of Engineering - Research topics: ML Theory, Social Science, Security, Ethics - Labs: Security Lab (SeclaBU) - Website: https://www.bu.edu/eng/profile/gianluca-stringhini-ph-d/ - Reach out: email gian@bu.edu ### 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 Ha… - Departments: Electrical and Computer Engineering, College of Engineering - Research topics: ML Theory, Robotics, Healthcare, Neuroscience - Labs: Network Optimization and Control Laboratory, Rafik B. Hariri Institute for Computing and Computational Science & Engineering - Website: https://www.bu.edu/eng/profile/ioannis-paschalidis/ - Reach out: email yannisp@bu.edu ### 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, a… - Departments: Mechanical Engineering - Research topics: Robotics - Labs: Robotics & Autonomous Systems Teaching and Innovation Center (RASTIC) - Website: https://www.bu.edu/eng/profile/kenn-sebesta/ - Reach out: email ksebesta@bu.edu ### 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,… - Departments: Electrical and Computer Engineering, College of Engineering - Research topics: ML Theory, Data Science, Physical Sciences - Labs: Computational Imaging Systems Lab - Website: https://www.bu.edu/eng/profile/lei-tian/ - Reach out: email leitian@bu.edu ### 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, e… - Departments: Writing Program - Research topics: Generative AI/Tools, Ethics, Education - Website: https://www.bu.edu/writingprogram/profile/pary-fassihi/ - Reach out: email fassihi@bu.edu ### 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… - Departments: Computer Science - Research topics: ML Theory, Healthcare - Website: https://www.bu.edu/met/profile/reza-rawassizadeh/ - Reach out: email rezar@bu.edu ### 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 diagnosi… - Departments: Mechanical Engineering, Materials Science and Engineering, College of Engineering - Research topics: Robotics - Labs: Material Robotics Laboratory - Website: https://www.bu.edu/eng/profile/sheila-russo-phd/ - Reach out: email russos@bu.edu ### 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… - Departments: Medicine, School of Medicine - Research topics: ML Theory, Healthcare, Neuroscience - Labs: Kolachalama Lab - Website: https://www.bu.edu/cs/profiles/vkola/ - Reach out: email vkola@bu.edu ### 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 appl… - Departments: Electrical and Computer Engineering, College of Engineering - Research topics: ML Theory, Robotics, AI Safety - Labs: Dependable Computing Laboratory - Website: https://www.bu.edu/hic/profile/wenchao-li/ - Reach out: email wenchao@bu.edu ### 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 prope… - Departments: Computing & Data Sciences, Faculty of Computing & Data Sciences - Research topics: ML Theory, Data Science - Website: https://onak.pl/ - Reach out: email konak@bu.edu ### 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 cognitio… - Departments: Linguistics, Computer Science, Computing & Data Sciences - Research topics: NLP/LLMs, ML Theory, HCI - Labs: tinlab - Website: https://najoung.kim/ - Reach out: email najoung@bu.edu ### 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 t… - Departments: Computer Science, Computing & Data Sciences - Research topics: Generative AI/Tools, NLP/LLMs, Data Science - Labs: AI Development Accelerator (AIDA) - Website: https://www.cs.bu.edu/fac/byers/ - Reach out: email byers@bu.edu ### 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 hol… - Departments: Hariri Institute - Research topics: Generative AI/Tools, Computer Vision, Robotics - Labs: Software & Application Innovation Lab (SAIL) - Website: https://www.bu.edu/hic/profile/ian-westmacott-phd/ - Reach out: email ianw@bu.edu ### 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… - Departments: Hariri Institute, BU Spark! - Research topics: Generative AI/Tools, NLP/LLMs - Labs: Software & Application Innovation Lab (SAIL) - Reach out: email am5815@bu.edu ### 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 na… - Departments: Computing & Data Sciences, BU Spark! - Research topics: Data Science - Website: https://www.bu.edu/cds-faculty/profile/zcranmer/ - Reach out: email zcranmer@bu.edu ### 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 includi… - Departments: College of Fine Arts, BU Spark! - Research topics: HCI - Website: https://www.bu.edu/cfa/about/contact-directions/directory/james-grady/ - Reach out: email jjgrady@bu.edu