367 resources shown
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.
A student organization focused on ensuring AI benefits everyone, running cohort-based fellowships in technical alignment and AI policy alongside a policy-analysis lab.
A cross-disciplinary research initiative developing computational models for machine intelligence: systems that reliably make decisions, reason about data, and communicate with humans.
A cross-disciplinary initiative facilitating research on AI and human learning across ages and contexts, drawing on computing, education, and social-science perspectives.
A research collaborative evaluating how generative AI tools affect K-12 learning outcomes through independent studies conducted with EdTech industry partners.
A media-focused research group applying machine learning, natural language processing, and computer vision to study how emerging media shape mass and interpersonal communication.
A machine-learning research group building explainable, data-efficient models for medical image analysis, with attention to multimodal fusion and causal inference.
A computational biology research center developing computer-assisted methods to analyze and design the structure, function, and regulation of biological macromolecules.
A bioinformatics-focused research group bridging AI and biomedical science, developing machine-learning algorithms to decode, model, and reprogram genomic and biological systems.
A business-analytics research group extracting consumer-behavior and market insights from text data using causal inference, interpretable ML, and neural language processing.
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.
A machine-learning research group developing methods that work under resource constraints and limited supervision, with related projects on bias mitigation and network analysis.
A computer-vision research group developing methods for image and video analysis, machine learning, and human-computer interaction across medical and scientific applications.
A computer-graphics research group focused on computational fabrication, designing algorithms that connect digital 3D models to physically buildable objects and structures.
A computer-vision research group building camera-based sensing systems that count and locate people in large indoor spaces using overhead fisheye imagery.
A university-wide initiative guiding responsible generative-AI adoption across BU, providing supported AI tools, training, and events for students, faculty, and staff.
A computational-biology research group using the mathematics of machine learning to design biological experiments that reveal how cells and tissues are organized.
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.
A climate-focused research group developing interpretable AI methods to study Earth system variability, predictability, and change across time and space.
An experimental robotics facility housing a motion-capture system, autonomous ground and aerial vehicles, and an on-site workshop for building robots.
An interdisciplinary engineering center studying the science of autonomy, robotic vehicles and manipulators, and micron-scale robots that manipulate living cells.
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.
A formal-methods research group pairing computational proof techniques with machine learning to build safe, reliable, and secure hardware and software systems.
A business-school research initiative examining how generative AI affects firms, operations, markets, and work, including large language model reliability and algorithmic bias.
An economics-focused research group studying how AI and digital platforms reshape hiring, labor-market matching, and work, using platform data and randomized experiments.
A control-theory research group combining formal methods, dynamics, and machine learning to design provably correct behavior for robots and autonomous vehicles.
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.
A security-focused research group applying program analysis, machine learning, and computational social science to software vulnerabilities and harmful online activity.
A department-wide research community whose faculty build intelligent systems that learn to make decisions, reason about data, and communicate with people.
A soft-robotics research group designing flexible, sensorized surgical instruments and the micro-scale manufacturing techniques needed to build them for minimally invasive procedures.
A robotics-focused research group designing collaborative robot teams that make fast, decentralized decisions and adapt to unknown agents and environments.
A research group focused on optimization, machine learning, and control, developing data-driven methods for networks, autonomous systems, and health analytics.
A neuroengineering-focused research group developing AI algorithms that analyze neuroimaging, electrophysiology, and genetics data to understand and treat brain disorders.
A computing-systems research group applying machine learning to energy-efficient computing, from large-scale system analytics to sustainable AI data center management.
A robotics teaching and innovation facility where engineering students design, build, and test robotic systems with staff guidance and mentoring.
A computer-science research group spanning computer vision, graphics, and human-computer interaction, with machine learning methods applied across visual computing problems.
