Massachusetts Institute of Technology

Joshua TenenbaumProfessor

Studies computational cognitive science and cognitive AI, building computational models of human cognition with machine learning.

• Computational neuroscience & cognition

Daniela RusDirector, CSAIL; Panasonic Professor

Studies robotics, including soft robots, self-driving cars for mobility on demand, and rapid robot design and fabrication.

• Autonomous vehicles & drones
• Soft, surgical & micro robots
• Geometry processing & modeling

Tommi JaakkolaThomas M. Siebel Distinguished Professor

Develops machine learning methods and theory for generating semi-structured data such as molecules and proteins, including the BoltzGen protein design model.

• Learning theory & optimization

Leslie KaelblingPanasonic Professor

Studies robotics, machine learning, and planning under uncertainty.

• Planning, control & multi-robot systems
• Probabilistic & causal inference

Tomás Lozano-PérezProfessor

Integrates machine learning with task, motion, and decision-theoretic planning for robotic manipulation.

• Manipulation & robot learning
• Planning, control & multi-robot systems

Pulkit AgrawalAssociate Professor

Studies robot learning, including reinforcement learning, dexterous manipulation, and self-supervised learning of sensorimotor skills.

• Manipulation & robot learning
• Reinforcement learning
• Generative & foundation models

Gabriele FarinaAssistant Professor

Develops foundations for learning and decision-making under imperfect information, combining game theory with machine learning and optimization for…

• Learning theory & optimization
• Reinforcement learning

Song HanAssociate Professor

Develops efficient deep learning, including model compression, quantization, and hardware-software co-design for LLM inference.

• Efficient training & inference
• Accelerators, chips & architecture

Yoon KimAssociate Professor

Studies natural language processing and machine learning, including efficient training and deployment of large-scale models.

• Efficient training & inference

Jacob AndreasITT Career Development Professor in Computer Technology; Associate Professor of EECS

Studies the computational foundations of language learning, machine learning from natural-language guidance, and tools for interpreting black-box models.

Wojciech MatusikCadence Design Systems Professor

Builds AI for the physical world, combining representations, physics simulation, and fabrication hardware such as self-monitoring 3D printers to design…

• Physics-based simulation & animation
• Geometry processing & modeling
• Physics, climate & scientific computing

Phillip IsolaAssociate Professor

Studies how intelligence works and why we represent the world as we do, building machine learning systems for vision and language that replicate these…

• Vision-language & multimodal

Patrick JailletDugald C. Jackson Professor of Electrical Engineering and Computer Science

Studies online optimization and learning, and sequential decision-making under uncertainty.

• Reinforcement learning
• Learning theory & optimization

Asuman OzdaglarEECS Department Head; MIT Schwarzman College of Computing Deputy Dean of Academics; MathWorks Professor

Studies optimization, game theory, and machine learning, including distributed optimization, game-theoretic learning, and multi-agent reinforcement learning.

• Learning theory & optimization
• Reasoning & neuro-symbolic AI
• Planning, control & multi-robot systems

Marzyeh GhassemiGermeshausen Career Development Professor; Associate Professor

Develops machine learning to understand and improve health in ways that are robust, private, and fair.

• Medical imaging & healthcare AI

Russ TedrakeToyota Professor, Electrical Engineering and Computer Science, Mechanical Engineering, and Aeronautics and Astronautics

Studies dynamics and control of legged robots, humanoids, and dexterous manipulators, and develops the Drake toolbox for optimization-based robot design.

• Legged locomotion & humanoids
• Manipulation & robot learning
• Learning theory & optimization

Antonio TorralbaFaculty Head, AI+D; Delta Electronics Professor

Studies computer vision, machine learning, and human visual perception, including multisensory perception and understanding neural networks.

• Recognition, detection & segmentation
• Robot perception & SLAM

Paul LiangSony Corporation Career Development Professor of Media Arts and Sciences; Assistant Professor

Develops foundations of multisensory and self-evolving AI that integrate diverse sensory channels, and interactive AI that augments human capabilities.

Ankur MoitraAssociate Director of the Institute for Data Systems & Society; Francis Wright Davis Professor of Mathematics

Designs algorithms with provable guarantees for machine learning problems, including unsupervised learning, topic models, and robustness.

• Trustworthy & safe ML

Caroline UhlerAndrew (1956) and Erna Viterbi Professor; Professor of EECS and in IDSS

Develops machine learning methods that integrate data modalities and infer causal relationships, applied to regulatory circuits in cells and tissues.

• Probabilistic & causal inference