Research

Impact Areas

Lead

Daniela Rus

+11

Daniela Rus

Research Group

Interactive Robotics Group

The Interactive Robotics Group aims to imagine the future of work by designing collaborative robot teammates that enhance human capability.

Julie Shah

Leads

Julie Shah

Research Areas

Impact Areas

Lead

Julie Shah

Research Group

Learning and Intelligent Systems

We conduct interdisciplinary research aimed at discovering the principles underlying the design of artificially intelligent robots.

Leslie Kaelbling

Tomas Lozano-Perez

Leads

Leslie Kaelbling

Tomas Lozano-Perez

Research Areas

Impact Areas

Lead

Leslie Kaelbling

Tomas Lozano-Perez

Leslie Kaelbling

Tomas Lozano-Perez

Research Group

Machine Learning

We work on a variety of topics spanning theoretical foundations, algorithms, and applications.

Leads

Tamara Broderick

Tommi Jaakkola

Stefanie Jegelka

Leslie Kaelbling

David Sontag

Research Areas

Impact Areas

Lead

Tamara Broderick

Tommi Jaakkola

Stefanie Jegelka

Leslie Kaelbling

David Sontag

Research Group

Marine Robotics Group

Our projects are centered around the problems of navigation and mapping for autonomous mobile robots operating in underwater and terrestrial environments.

John Leonard

Leads

John Leonard

Research Areas

Impact Areas

Lead

John Leonard

Research Group

Robot Locomotion Group

We research building machines which exploit their natural dynamics to achieve extraordinary agility and efficiency.

Russ Tedrake

Leads

Russ Tedrake

Research Areas

Impact Areas

Lead

Russ Tedrake

Research Group

Robust Robotics Group

We build unmanned vehicles that can fly and drive without maps or GPS.

Nicholas Roy

Leads

Nicholas Roy

Research Areas

Impact Areas

Lead

Nicholas Roy

Research Group

Geometric Data Processing Group

Our group studies geometric problems in computer graphics, computer vision, machine learning, optimization, and other disciplines.

Justin Solomon

Leads

Justin Solomon

Research Areas

Impact Areas

Lead

Justin Solomon

Research Center

Internet Policy Research Initiative

Our mission is to work with policy makers and cybersecurity technologists to increase the trustworthiness and effectiveness of interconnected digital systems.

Leads

Daniel Weitzner

Hal Abelson

David Clark

Lalana Kagal

Karen Sollins

Gerald Sussman

Research Areas

Impact Areas

Lead

Daniel Weitzner

Hal Abelson

David Clark

Lalana Kagal

Karen Sollins

Gerald Sussman

Community of Research

The Systems CoR is focused on building and investigating large-scale software systems that power modern computers, phones, data centers, and networks, including operating systems, the Internet, wireless networks, databases, and other software infrastructure.

+21

Sam Madden

Leads

Sam Madden

Research Areas

Computer Architecture

Impact Areas

Lead

Sam Madden

+21

Sam Madden

Community of Research

Computing & Society Community of Research

This community is interested in understanding and affecting the interaction between computing systems and society through engineering, computer science and public policy research, education, and public engagement.

Daniel Weitzner

Leads

Daniel Weitzner

Research Areas

Impact Areas

Lead

Daniel Weitzner

Community of Research

Vertical AI Community of Research

This CoR takes a unified approach to cover the full range of research areas required for success in artificial intelligence, including hardware, foundations, software systems, and applications.

Martin Rinard

Leads

Martin Rinard

Research Areas

Impact Areas

Lead

Martin Rinard

Community of Research

Visual Computing Community of Research

The shared mission of Visual Computing is to connect images and computation, spanning topics such as image and video generation and analysis, photography, human perception, touch, applied geometry, and more.

+10

Ruth Rosenholtz

Leads

Ruth Rosenholtz

Research Areas

Impact Areas

Lead

Ruth Rosenholtz

+10

Ruth Rosenholtz

Research Group

Vision Group

Our researchers create state-of-the-art systems to better recognize objects, people, scenes, behaviors and more, with applications in health-care, gaming, tagging systems and more.

Leads

Ted Adelson

Fredo Durand

John Fisher

William Freeman

Polina Golland

Berthold Horn

Aude Oliva

Antonio Torralba

Eric Grimson

Research Areas

Impact Areas

Lead

Ted Adelson

Fredo Durand

John Fisher

William Freeman

Polina Golland

Berthold Horn

Aude Oliva

Antonio Torralba

Eric Grimson

29 Project Results matching all criteria

Project

Driver-Friendly Bilateral Control for Suppressing Traffic Instabilities

We are studying how best to implement bilateral control and make it acceptable to drivers

Berthold Horn

Leads

Berthold Horn

Research Areas

Impact Areas

Berthold Horn

Project

Artificial Co-driver

By observing driver in real road situations, we learn a computer assistant that can make driving easier, safer and more enjoyable.

Leads

Research Areas

Impact Areas

Model-Based Embedded and Robotics Systems Group

Project

Geordi: A Driver's Assistant for Risk-bounded Maneuvering

Our goal is to create an online risk-aware planner for vehicle maneuvers that can make driving safer and less stressful through a “parallel” autonomous system that assists the driver by watching for risky situations, and by helping the driver take proactive, compensating actions before they become crises.

Brian Williams

Leads

Brian Williams

Research Areas

Impact Areas

Brian Williams

Project

Printable Hydraulics

Printable Hydraulics allows fluid-actuated robots to be automatically fabricated using 3D printers.

Youbin Kim

Leads

Research Areas

Impact Areas

Youbin Kim

Project

Computational Multicopter Design

A system that can help you to design our own drone!

Tao Du

Leads

Tao Du

Research Areas

Impact Areas

Tao Du

Project

Characterizing the Sensitivity of Vision-in-the-Loop Driving Controllers Using CG

We work on understanding and improving vision algorithms used for self driving cars, by introducing synthetic data-sets to the loop.

Leads

Research Areas

Impact Areas

Project

Peripheral Vision and Driver Behavior

Our goal is to understand what drivers can perceive when they are not attending to the road ahead and the consequences of their perceptions for safety.

Leads

Research Areas

Impact Areas

Project

Robotic Planning and Manipulation with Force Information

Our goal is to allow planners to exploit the forces and contacts between objects so as to carry out complex manipulation tasks in the presence of uncertainty.

Leads

Gustavo N. Goretkin

Leslie Kaelbling

Tomas Lozano-Perez

Research Areas

Impact Areas

Networks and Mobile Systems

Project

Aggregate Congestion Control

Develop a method for sending persistently backlogged traffic on the Internet while adapting to link conditions dynamically.

Akshay Narayan

Francis Cangialosi

Leads

Akshay Narayan

Francis Cangialosi

Research Areas

Impact Areas

Akshay Narayan

Francis Cangialosi

Project

The Car Can Explain!

Developing techniques to allow self-driving cars and other AI-driven systems to explain behaviors and failures.

Gerald Sussman

Lalana Kagal

Leads

Gerald Sussman

Lalana Kagal

Research Areas

Impact Areas

Cybersecurity

Gerald Sussman

Lalana Kagal

Project

Task and Motion Planning for Autonomous Robots

Our goal is to design algorithms that enable robots to operate in human environments by simultaneously reasoning about high-level task actions as well as low-level motions.

Leads

Caelan Garrett

Leslie Kaelbling

Tomas Lozano-Perez

Research Areas

Impact Areas

Project

Deterministic Algorithms for Robotic Task and Motion Planning

Our goal is to investigate deterministic algorithms for robotic task and motion planning.

Leads

Research Areas

Impact Areas

Project

Safety Standards for Autonomous Vehicles

In this project, we aim to develop a framework that can ensure and certify the safety of an autonomous vehicle. By leveraging research from the area of formal verification, this framework aims to assess the safety, i.e., free of collisions, of a broad class of autonomous car controllers/planners for a given traffic model.

Leads

Lucas Liebenwein

Wilko Schwarting

Daniela Rus

Research Areas

Impact Areas

Project

SoFi - The Soft Robotic Fish

Exploration of underwater life with an acoustically controlled soft robotic fish

Joseph DelPreto

Leads

Joseph DelPreto

Research Areas

Impact Areas

Joseph DelPreto

Project

Wearable Blind Navigation

We enable independent navigation for visually impaired users through a wearable feedback system using time-of-light sensors or depth cameras.

Leads

Research Areas

Impact Areas

Project

Autonomous Vehicle Databases

Data Systems Group

The impending success of AV technology will create vehicles that collect sensor data at a high rate.

Michael Stonebraker

Sam Madden

Leads

Michael Stonebraker

Sam Madden

Research Areas

Impact Areas

Michael Stonebraker

Sam Madden

Project

Drones that Drive

Multi-robot path planning for robot swarms that can both fly and drive

Leads

Research Areas

Impact Areas

Project

Better Models for Ride-Sharing

Traffic is not just a nuisance for drivers: It’s also a public health hazard and bad news for the economy.

Leads

Research Areas

Impact Areas

Project

Robust Intelligent Robots

How can a mobile-manipulation robot operate robustly and flexibly in complicated uncertain environments, such as households and disaster zones.

Leslie Kaelbling

Tomas Lozano-Perez

Leads

Leslie Kaelbling

Tomas Lozano-Perez

Research Areas

Impact Areas

Leslie Kaelbling

Tomas Lozano-Perez

Project

Self-Driving Vehicles

We want to help to make driving more comfortable, environmentally friendly and above all safer!

Leads

Russ Tedrake

John Leonard

Daniela Rus

Sertac Karaman

Research Areas

Impact Areas

Project

Planning in Congestion for Autonomous Vehicles

Our goal is to develop an autonomous vehicle control strategy that adapts on-line to varying levels of congestion in the environment.

Leads

Wilko Schwarting

Sertac Karaman

Daniela Rus

Research Areas

Impact Areas

Project

Robust Learning for Autonomous Vehicles

Our goal is to create a theoretical framework and effective machine learning algorithms for robust, reliable control of autonomous vehicles. Key threads include developing metrics of confidence; and designing deep learning algorithms for parallel autonomy.

Daniela Rus

Alexander Amini

Leads

Daniela Rus

Alexander Amini

Research Areas

Impact Areas

Daniela Rus

Alexander Amini

Project

Socially-Compliant Behavior for Autonomous Driving

Bringing human-like decision making to autonomous driving.

Leads

Wilko Schwarting

Sertac Karaman

Javier Alonso-Mora

Daniela Rus

Research Areas

Impact Areas

Project

PrivacyML - A Privacy Preserving Framework for Machine Learning

We are developing a general framework that enforces privacy transparently enabling different kinds of machine learning to be developed that are automatically privacy preserving.

Lalana Kagal

Vaikkunth Mugunthan

Leads

Lalana Kagal

Vaikkunth Mugunthan

Research Areas

Impact Areas

Lalana Kagal

Vaikkunth Mugunthan

29 People Results matching all criteria

PI
Core/Dual

Hal Abelson

Professor

Programming, privacy, App Inventor

E hal@mit.edu

T 253-5856

Lead

MIT App Inventor

Member

Programming, privacy, App Inventor

PI
Core/Dual

Ted Adelson

Professor

Vision, touch sensing, robotics

E adelson@csail.mit.edu

T 253-0645

Lead

Blood Pressure Imager

Member

Vision, touch sensing, robotics

Alexander Amini

Graduate Student

PhD Candidate. Deep Learning; Robotics

E Amini@mit.edu

Lead

Member

Noria: a new data-flow system for web applications

PhD Candidate. Deep Learning; Robotics

Brandon Araki

Graduate Student

E araki@csail.mit.edu

Jonathan Behrens

Graduate Student

E behrensj@mit.edu

RM 32-G978B

Member

Parallel and Distributed Operating Systems

Noam Buckman

Graduate Student

PhD Candidate. Autonomous vehicles. Multi-robot systems.

E nbuckman@mit.edu

Member

Sensorized Soft Electric Hands with Handed Shearing Auxetics

PhD Candidate. Autonomous vehicles. Multi-robot systems.

Lillian Chin

Graduate Student

E ltchin@mit.edu

Lead

Member

PI
Core/Dual

Fredo Durand

Professor

Vision, graphics, computational photography

E fredo@csail.mit.edu

T 253-7223

Lead

Computational Understanding of Visualizations and Graphic Designs

Member

Computational Bounce Flash for Indoor Portraits

Halide

Vision, graphics, computational photography

R. David Edelman

Director, Project on Technology, Economy & National Security

Machine learning, cybersecurity, governance

E rde@mit.edu

T 258-6389

Machine learning, cybersecurity, governance

Gregory Falco

Research Affiliate

Dr. Falco is a hacker and expert in IoT and IIoT cybersecurity.

E gfalco@mit.edu

Dr. Falco is a hacker and expert in IoT and IIoT cybersecurity.

Sue Felshin

Research Scientist

E sfelshin@csail.mit.edu

T 253-2965

Lead

Member

PI
Core/Dual

William Freeman

Professor

Vision, machine learning, Bayesian modeling

E billf@csail.mit.edu

T 253-8828

Lead

Single-Image 3D Interpreter Network

Member

Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks

Learning the Arrow of Time from Videos

3D Generative Adversarial Networks

Vision, machine learning, Bayesian modeling

Igor Gilitschenski

Research Scientist

E igilitschenski@mit.edu

Member

Spoken Language Systems Group

PI
Core/Dual

Jim Glass

Senior Research Scientist

speech and language processing

E glass@mit.edu

T 253-1640

Lead

Designing Information-Rich Embedding Spaces

Unsupervised Learning of Interpretable Representations from Sequential Data

Fact-Checking and Reasoning

Speaker Verification and Diarization

Automatic Speech Recognition

Language and Dialect Identification

Member

Using Computers to Eat Healthier

Low-Power Speech Processing Circuits

Crossing the Vision-Language Boundary

Unsupervised Speech Processing

Arabic Language Processing

Health-related Biomarkers from Speech

Community Question Answering

Understanding Language Representations in Deep Learning Models

speech and language processing

PI
Core/Dual

Berthold Horn

Professor

Vision, computational imaging

E bkph@csail.mit.edu

T 253-5863

Lead

Driver-Friendly Bilateral Control for Suppressing Traffic Instabilities

Member

EQ-Radio: Emotion Recognition using Wireless Signals

Vision, computational imaging

PI
Core/Dual

Dina Katabi

Professor

Wireless, networks, machine learning

E dina@csail.mit.edu

T 324-6027

Lead

Networks at MIT

Member

Vertical AI Community of Research

Wireless, networks, machine learning

PI
Core/Dual

Boris Katz

Principal Research Scientist

Natural language processing

E boris@csail.mit.edu

T 253-6032

Lead

Semantic Parsing using Vision

Generating Plans for Agents using Video and Language

Inferring “Theory of Mind” with vision and language

Artificial Social Intelligence for Successful Teams (ASIST)

Member

Center for Brains, Minds and Machines

Natural language processing

PI
Core/Dual

John Leonard

Professor

Robotics, navigation/mapping, self-driving cars

E jleonard@csail.mit.edu

T 253-5305

Lead

Marine Robotics Group

Member

Robotics, navigation/mapping, self-driving cars

Lucas Liebenwein

Graduate Student

Student and Researcher | Robotics, AI | Advanced Autonomy

E lucasl@mit.edu

RM 32-376C

Lead

Member

Inferring 3D Shape Distributions for Robot Perception and Planning

Student and Researcher | Robotics, AI | Advanced Autonomy

PI
Core/Dual

Nicholas Roy

Professor

Robotics, autonomy, artificial intelligence, motion planning

E nickroy@csail.mit.edu

T 253-2517

Lead

Robust Robotics Group

Member

Enabling Semantic Understanding for Autonomous Marine Robots

Robotics, autonomy, artificial intelligence, motion planning

PI
Core/Dual

Daniela Rus

Director

CSAIL director, robotics, AI, data science, privacy

E rus@csail.mit.edu

T 258-7567

RM 32/ 32-368/ 374

Lead

Social Network Extraction from GPS Datasets with Coresets

Practical Secure Computation

Soft Contact Modeling

Brain-Controlled Robots

M-Blocks Modular Robotics

Robot Compiler

Distributed Robot Garden

Route and Motion Planning for Mobility-on-Demand with Rules of the Road

Member

Social Network Extraction from GPS Datasets with Coresets

Task-Driven Co-Optimization Of Articulated Robots

Wearable Blind Navigation

Drones that Drive

Better Models for Ride-Sharing

SoFi - The Soft Robotic Fish

Controlling drones and other robots with gestures

Using Muscle Signals to Lift Objects with Robots

Helping robots learn using demonstrations

CSAIL director, robotics, AI, data science, privacy

Ryan Sander

Graduate Student

Graduate Research Assistant in MIT Distributed Robotics Laboratory

E rmsander@csail.MIT.EDU

Graduate Research Assistant in MIT Distributed Robotics Laboratory

Wilko Schwarting

Graduate Student

E wilkos@mit.edu

Lead

Member

PI
Core/Dual

Gerald Sussman

Professor

Artificial intelligence, supercomputers

E gjs@csail.mit.edu

T 253-5874

RM 32/ 32-G508/ G514

Lead

Sussman Lab

The Car Can Explain!

Member

Artificial intelligence, supercomputers

29 News Results matching all criteria

AI & ML Transportation

December 10 '20

Explained: Levels of autonomy in self-driving cars

A six-level system classifies the varying degrees of vehicle autonomy

Explained: Levels of autonomy in self-driving cars

A neural network learns when it should not be trusted

AI & ML Robotics Transportation

November 24 '20

A neural network learns when it should not be trusted

A faster way to estimate uncertainty in AI-assisted decision-making could lead to safer outcomes.

A neural network learns when it should not be trusted

Algorithms & Theory Robotics Transportation

October 26 '20

Autonomous boats could be your next ride

Five years in the making, MIT’s autonomous floating vessels get a size upgrade and learn a new way to communicate aboard the waters.

Autonomous boats could be your next ride

AI & ML Robotics Cybersecurity Internet of Things Transportation

January 13 '20

WaPo op-ed: how to regulate AI properly

In a Washington Post op-ed, CSAIL's R. David Edelman outlines how to regulate AI properly

WaPo op-ed: how to regulate AI properly

AI & ML Robotics Manufacturing Transportation

October 30 '19

Self-transforming robot blocks jump, spin, flip, and identify each other

Developed at MIT’s Computer Science and Artificial Intelligence Laboratory, a team of robots can self-assemble to form different structures with applications in inspection, disaster response, and manufacturing

Self-transforming robot blocks jump, spin, flip, and identify each other

Algorithms & Theory AI & ML Graphics & Vision Big Data Transportation

October 29 '19

Deep learning with point clouds

Research aims to make it easier for self-driving cars, robotics, and other applications to understand the 3D world.

Deep learning with point clouds

Algorithms & Theory AI & ML Robotics Transportation

August 29 '19

MIT’s fleet of autonomous boats can now shapeshift

New capabilities allow “roboats” to change configurations to form pop-up bridges, stages, and other structures.

MIT’s fleet of autonomous boats can now shapeshift

Transportation

August 22 '19

Optimus Ride’s autonomous system makes self-driving vehicles a reality

MIT startup’s unique approach to improving human mobility is helping it gain traction in a competitive landscape.

Optimus Ride’s autonomous system makes self-driving vehicles a reality

Algorithms & Theory Security & Cryptography Transportation

July 23 '19

Making it easier to program and protect the web

Professor Adam Chlipala builds tools to help programmers more quickly generate optimized, secure code.

Making it easier to program and protect the web

Algorithms & Theory Robotics Transportation

June 27 '19

Autonomous boats can target and latch onto each other

Fleet of “roboats” could collect garbage or self-assemble into floating structures in Amsterdam’s many canals.

Autonomous boats can target and latch onto each other

Algorithms & Theory AI & ML Computational Biology Computer Architecture Graphics & Vision Human-Computer Interaction Programming Languages & Software Engineering Robotics Security & Cryptography Systems & Networking Cybersecurity Education Energy Entertainment Health Care Manufacturing Transportation Wireless

June 27 '19

CSAIL hosts first-ever TEDxMIT

Speakers — all women — discuss everything from gravitational waves to robot nurses

CSAIL hosts first-ever TEDxMIT

Algorithms & Theory AI & ML Cybersecurity Health Care Internet of Things Manufacturing Transportation Wireless

February 12 '19

MIT CSAIL holds trustworthy AI event with Microsoft

Workshop explores technical directions for making AI safe, fair, and understandable

MIT CSAIL holds trustworthy AI event with Microsoft

Algorithms & Theory AI & ML Robotics Transportation

February 01 '19

Engineers program marine robots to take calculated risks

Algorithm could help autonomous underwater vehicles explore risky but scientifically-rewarding environments.

Engineers program marine robots to take calculated risks

Algorithms & Theory AI & ML Robotics Transportation

January 25 '19

Identifying artificial intelligence “blind spots”

Model identifies instances when autonomous systems have learned from examples that may cause dangerous errors in the real world.

Identifying artificial intelligence “blind spots”

Algorithms & Theory AI & ML Programming Languages & Software Engineering Transportation

December 19 '18

Cambridge Mobile Telematics Raises $500M from SoftBank Vision Fund

AI & ML Robotics Health Care Transportation

November 01 '18

Fleets of drones could aid searches for lost hikers

System allows drones to cooperatively explore terrain under thick forest canopies where GPS signals are unreliable.

Fleets of drones could aid searches for lost hikers

AI & ML Transportation

October 25 '18

Honda Research Institute Launches “Curious Minded Machine” Research Collaboration with MIT, University of Pennsylvania and University of Washington

Honda Research Institute USA seeks to develop intelligent systems that use curiosity to understand people’s needs and empower human capability through cross-disciplinary research that aims to advance breakthroughs in artificial cognition.

Honda Research Institute Launches “Curious Minded Machine” Research Collaboration with MIT, University of Pennsylvania and University of Washington

model helps robots naviagte like humans 1

Algorithms & Theory AI & ML Robotics Transportation

October 04 '18

Model helps robots navigate more like humans do

In simulations, robots move through new environments by exploring, observing, and drawing from learned experiences.

Model helps robots navigate more like humans do

AI & ML Education Health Care Manufacturing Transportation Wireless

October 03 '18

Google AI’s Jeff Dean discusses using deep learning to solve challenging problems

Google AI’s Jeff Dean has a seemingly straightforward objective: he wants to use a collection of trainable mathematical units organized in layers to solve complicated tasks that will ultimately benefit many parts of society.

Google AI’s Jeff Dean discusses using deep learning to solve challenging problems

AI & ML Education Health Care Manufacturing Transportation Wireless

October 01 '18

Deep Learning to Solve Challenging Problems - Dr. Jeff Dean

October 1, 2018 - Jeff Dean of Google gave a CSAIL seminar titled "Deep Learning to Solve Challenging Problems."

Deep Learning to Solve Challenging Problems - Dr. Jeff Dean

Algorithms & Theory Entertainment Health Care Manufacturing Transportation

May 25 '18

Demaine gives Congressional briefing on intersection of origami and computer science

MIT professor discusses using paper-folding for applications in manufacturing, medicine, and robotics

Demaine gives Congressional briefing on intersection of origami and computer science

Algorithms & Theory AI & ML Robotics Transportation

May 23 '18

Making driverless cars change lanes more like human drivers do

Algorithm computes “buffer zones” around autonomous vehicles and reassess them on the fly.

Making driverless cars change lanes more like human drivers do

AI & ML Graphics & Vision Robotics Transportation

May 07 '18

Self-driving cars for country roads

For all the progress made in self-driving technologies, there still aren’t many places where they can actually drive. Companies like Google only test their fleets in major cities where they’ve spent countless hours meticulously labeling the exact 3-D positions of lanes, curbs, off-ramps, and stop signs.

Self-driving cars for country roads

AI & ML Robotics Manufacturing Transportation

March 21 '18

Soft robotic fish swims alongside real ones in coral reefs

Made of silicone rubber, CSAIL’s “SoFi” could enable a closer study of aquatic life.

Soft robotic fish swims alongside real ones in coral reefs

14 Group Results

Community of Research

Computing & Society Community of Research

Daniel Weitzner

Leads

Daniel Weitzner

Research Areas

Impact Areas

Lead

Daniel Weitzner

Research Group

Distributed Robotics Laboratory

We aim to develop the science of autonomy toward a future with robots and AI systems integrated into everyday life, supporting people with cognitive and physical tasks.

+11

Daniela Rus

Leads

Daniela Rus

Research Areas

Impact Areas

Lead

Daniela Rus

+11

Daniela Rus

Research Group

Geometric Data Processing Group

Our group studies geometric problems in computer graphics, computer vision, machine learning, optimization, and other disciplines.

Justin Solomon

Leads

Justin Solomon

Research Areas

Impact Areas

Lead

Justin Solomon

Research Group

Interactive Robotics Group

The Interactive Robotics Group aims to imagine the future of work by designing collaborative robot teammates that enhance human capability.

Julie Shah

Leads

Julie Shah

Research Areas

Impact Areas

Lead

Julie Shah

Research Center

Internet Policy Research Initiative

Our mission is to work with policy makers and cybersecurity technologists to increase the trustworthiness and effectiveness of interconnected digital systems.

Leads

Daniel Weitzner

Hal Abelson

David Clark

Lalana Kagal

Karen Sollins

Gerald Sussman

Research Areas

Impact Areas

Lead

Daniel Weitzner

Hal Abelson

David Clark

Lalana Kagal

Karen Sollins

Gerald Sussman

Research Group

Learning and Intelligent Systems

We conduct interdisciplinary research aimed at discovering the principles underlying the design of artificially intelligent robots.

Leslie Kaelbling

Tomas Lozano-Perez

Leads

Leslie Kaelbling

Tomas Lozano-Perez

Research Areas

Impact Areas

Lead

Leslie Kaelbling

Tomas Lozano-Perez

Leslie Kaelbling

Tomas Lozano-Perez

Research Group

Machine Learning

We work on a variety of topics spanning theoretical foundations, algorithms, and applications.

Leads

Tamara Broderick

Tommi Jaakkola

Stefanie Jegelka

Leslie Kaelbling

David Sontag

Research Areas

Impact Areas

Lead

Tamara Broderick

Tommi Jaakkola

Stefanie Jegelka

Leslie Kaelbling

David Sontag

Research Group

Marine Robotics Group

Our projects are centered around the problems of navigation and mapping for autonomous mobile robots operating in underwater and terrestrial environments.

John Leonard

Leads

John Leonard

Research Areas

Impact Areas

Lead

John Leonard

Research Group

Robot Locomotion Group

We research building machines which exploit their natural dynamics to achieve extraordinary agility and efficiency.

Russ Tedrake

Leads

Russ Tedrake

Research Areas

Impact Areas

Lead

Russ Tedrake

Research Group

Robust Robotics Group

We build unmanned vehicles that can fly and drive without maps or GPS.

Nicholas Roy

Leads

Nicholas Roy

Research Areas

Impact Areas

Lead

Nicholas Roy

Community of Research

Systems Community of Research

+21

Sam Madden

Leads

Sam Madden

Research Areas

Computer Architecture

Impact Areas

Lead

Sam Madden

+21

Sam Madden

Community of Research

Vertical AI Community of Research

This CoR takes a unified approach to cover the full range of research areas required for success in artificial intelligence, including hardware, foundations, software systems, and applications.

Martin Rinard

Leads

Martin Rinard

Research Areas

Impact Areas

Lead

Martin Rinard

Research Group

Vision Group

Our researchers create state-of-the-art systems to better recognize objects, people, scenes, behaviors and more, with applications in health-care, gaming, tagging systems and more.

Leads

Ted Adelson

Fredo Durand

John Fisher

William Freeman

Polina Golland

Berthold Horn

Aude Oliva

Antonio Torralba

Eric Grimson

Research Areas

Impact Areas

Lead

Ted Adelson

Fredo Durand

John Fisher

William Freeman

Polina Golland

Berthold Horn

Aude Oliva

Antonio Torralba

Eric Grimson

Community of Research

Visual Computing Community of Research

+10

Ruth Rosenholtz

Leads

Ruth Rosenholtz

Research Areas

Impact Areas

Networks and Mobile Systems

Lead

Ruth Rosenholtz

+10

Ruth Rosenholtz

29 Project Results

Project

Aggregate Congestion Control

Develop a method for sending persistently backlogged traffic on the Internet while adapting to link conditions dynamically.

Akshay Narayan

Francis Cangialosi

Leads

Akshay Narayan

Francis Cangialosi

Research Areas

Impact Areas

Human-Computer Interaction Community of Research

Akshay Narayan

Francis Cangialosi

Project

Alloy

Software Design Group

Alloy is a language for describing structures and a tool for exploring them. It has been used in a wide range of applications from finding holes in security mechanisms to designing telephone switching networks. Hundreds of projects have used Alloy for design analysis, for verification, for simulation, and as a backend for many other kinds of analysis and synthesis tools, and Alloy is currently being taught in courses worldwide.

Daniel Jackson

Leads

Daniel Jackson

Research Areas

Computer-Aided Programming

Impact Areas

Daniel Jackson

Project

An Interlock for Self Driving Cars

Software Design Group

Vertical AI Community of Research

Human-Computer Interaction Community of Research

Self-driving cars are likely to be safer, on average, than human-driven cars. But they may fail in new and catastrophic ways that a human driver could prevent. This project is designing a new architecture for a highly dependable self-driving car.

Daniel Jackson

Armando Solar-Lezama

Leads

Daniel Jackson

Armando Solar-Lezama

Research Areas

Impact Areas

Daniel Jackson

Armando Solar-Lezama

Project

Artificial Co-driver

By observing driver in real road situations, we learn a computer assistant that can make driving easier, safer and more enjoyable.

Leads

Research Areas

Impact Areas

Computation Structures Group

Project

Artificial Social Intelligence for Successful Teams (ASIST)

Computational Cognitive Science Group

Model-Based Embedded and Robotics Systems Group

Our goal is to develop a socially intelligent team coacher agent that helps humans communicate, strategize, and work together efficiently.

Leads

Howard Shrobe

Brian Williams

Boris Katz

Zhutian Yang

Research Areas

Computer Architecture

Impact Areas

Wireless

Project

Autonomous Vehicle Databases

Data Systems Group

The impending success of AV technology will create vehicles that collect sensor data at a high rate.

Michael Stonebraker

Sam Madden

Leads

Michael Stonebraker

Sam Madden

Research Areas

Impact Areas

Michael Stonebraker

Sam Madden

Project

Better Models for Ride-Sharing

Traffic is not just a nuisance for drivers: It’s also a public health hazard and bad news for the economy.

Leads

Research Areas

Impact Areas

Project

The Car Can Explain!

Developing techniques to allow self-driving cars and other AI-driven systems to explain behaviors and failures.

Gerald Sussman

Lalana Kagal

Leads

Gerald Sussman

Lalana Kagal

Research Areas

Impact Areas

Cybersecurity

Gerald Sussman

Lalana Kagal

Project

Characterizing the Sensitivity of Vision-in-the-Loop Driving Controllers Using CG

We work on understanding and improving vision algorithms used for self driving cars, by introducing synthetic data-sets to the loop.

Leads

Research Areas

Impact Areas

Project

Computational Multicopter Design

A system that can help you to design our own drone!

Tao Du

Leads

Tao Du

Research Areas

Impact Areas

Tao Du

Project

Deterministic Algorithms for Robotic Task and Motion Planning

Our goal is to investigate deterministic algorithms for robotic task and motion planning.

Leads

Research Areas

Impact Areas

Project

Driver-Friendly Bilateral Control for Suppressing Traffic Instabilities

We are studying how best to implement bilateral control and make it acceptable to drivers

Berthold Horn

Leads

Berthold Horn

Research Areas

Impact Areas

Berthold Horn

Project

Drones that Drive

Multi-robot path planning for robot swarms that can both fly and drive

Leads

Research Areas

Impact Areas

Model-Based Embedded and Robotics Systems Group

Project

Geordi: A Driver's Assistant for Risk-bounded Maneuvering

Brian Williams

Leads

Brian Williams

Research Areas

Impact Areas

Brian Williams

Project

Peripheral Vision and Driver Behavior

Our goal is to understand what drivers can perceive when they are not attending to the road ahead and the consequences of their perceptions for safety.

Leads

Research Areas

Impact Areas

Project

Planning in Congestion for Autonomous Vehicles

Our goal is to develop an autonomous vehicle control strategy that adapts on-line to varying levels of congestion in the environment.

Leads

Wilko Schwarting

Sertac Karaman

Daniela Rus

Research Areas

Impact Areas

Project

Printable Hydraulics

Printable Hydraulics allows fluid-actuated robots to be automatically fabricated using 3D printers.

Youbin Kim

Leads

Research Areas

Impact Areas

Youbin Kim

Project

PrivacyML - A Privacy Preserving Framework for Machine Learning

We are developing a general framework that enforces privacy transparently enabling different kinds of machine learning to be developed that are automatically privacy preserving.

Lalana Kagal

Vaikkunth Mugunthan

Leads

Lalana Kagal

Vaikkunth Mugunthan

Research Areas

Impact Areas

Lalana Kagal

Vaikkunth Mugunthan

Project

Robotic Planning and Manipulation with Force Information

Our goal is to allow planners to exploit the forces and contacts between objects so as to carry out complex manipulation tasks in the presence of uncertainty.

Leads

Gustavo N. Goretkin

Leslie Kaelbling

Tomas Lozano-Perez

Research Areas

Impact Areas

Project

Robust Intelligent Robots

How can a mobile-manipulation robot operate robustly and flexibly in complicated uncertain environments, such as households and disaster zones.

Leslie Kaelbling

Tomas Lozano-Perez

Leads

Leslie Kaelbling

Tomas Lozano-Perez

Research Areas

Impact Areas

Leslie Kaelbling

Tomas Lozano-Perez

Project

Robust Learning for Autonomous Vehicles

Daniela Rus

Alexander Amini

Leads

Daniela Rus

Alexander Amini

Research Areas

Impact Areas

Daniela Rus

Alexander Amini

Project

Route and Motion Planning for Mobility-on-Demand with Rules of the Road

Ensuring correct behavior of autonomous vehicles with respect to rules of the road

Sertac Karaman

Daniela Rus

Leads

Sertac Karaman

Daniela Rus

Research Areas

Impact Areas

Sertac Karaman

Daniela Rus

Project

Safety Standards for Autonomous Vehicles

Leads

Lucas Liebenwein

Wilko Schwarting

Daniela Rus

Research Areas

Impact Areas

Project

Self-Driving Vehicles

We want to help to make driving more comfortable, environmentally friendly and above all safer!

Leads

Russ Tedrake

John Leonard

Daniela Rus

Sertac Karaman

Research Areas

Impact Areas

29 People Results

PI
Core/Dual

Hal Abelson

Professor

Programming, privacy, App Inventor

E hal@mit.edu

T 253-5856

Lead

MIT App Inventor

Member

Programming, privacy, App Inventor

PI
Core/Dual

Ted Adelson

Professor

Vision, touch sensing, robotics

E adelson@csail.mit.edu

T 253-0645

Lead

Blood Pressure Imager

Member

Vision, touch sensing, robotics

Alexander Amini

Graduate Student

PhD Candidate. Deep Learning; Robotics

E Amini@mit.edu

Lead

Member

Noria: a new data-flow system for web applications

PhD Candidate. Deep Learning; Robotics

Brandon Araki

Graduate Student

E araki@csail.mit.edu

Jonathan Behrens

Graduate Student

E behrensj@mit.edu

RM 32-G978B

Member

Parallel and Distributed Operating Systems

Noam Buckman

Graduate Student

PhD Candidate. Autonomous vehicles. Multi-robot systems.

E nbuckman@mit.edu

Member

Sensorized Soft Electric Hands with Handed Shearing Auxetics

PhD Candidate. Autonomous vehicles. Multi-robot systems.

Lillian Chin

Graduate Student

E ltchin@mit.edu

Lead

Member

PI
Core/Dual

Fredo Durand

Professor

Vision, graphics, computational photography

E fredo@csail.mit.edu

T 253-7223

Lead

Computational Understanding of Visualizations and Graphic Designs

Member

Computational Bounce Flash for Indoor Portraits

Halide

Vision, graphics, computational photography

R. David Edelman

Director, Project on Technology, Economy & National Security

Machine learning, cybersecurity, governance

E rde@mit.edu

T 258-6389

Machine learning, cybersecurity, governance

Gregory Falco

Research Affiliate

Dr. Falco is a hacker and expert in IoT and IIoT cybersecurity.

E gfalco@mit.edu

Dr. Falco is a hacker and expert in IoT and IIoT cybersecurity.

Sue Felshin

Research Scientist

E sfelshin@csail.mit.edu

T 253-2965

Lead

Member

PI
Core/Dual

William Freeman

Professor

Vision, machine learning, Bayesian modeling

E billf@csail.mit.edu

T 253-8828

Lead

Single-Image 3D Interpreter Network

Member

Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks

Learning the Arrow of Time from Videos

3D Generative Adversarial Networks

Vision, machine learning, Bayesian modeling

Igor Gilitschenski

Research Scientist

E igilitschenski@mit.edu

Member

Spoken Language Systems Group

PI
Core/Dual

Jim Glass

Senior Research Scientist

speech and language processing

E glass@mit.edu

T 253-1640

Lead

Designing Information-Rich Embedding Spaces

Unsupervised Learning of Interpretable Representations from Sequential Data

Fact-Checking and Reasoning

Speaker Verification and Diarization

Automatic Speech Recognition

Language and Dialect Identification

Member

Using Computers to Eat Healthier

Low-Power Speech Processing Circuits

Crossing the Vision-Language Boundary

Unsupervised Speech Processing

Arabic Language Processing

Health-related Biomarkers from Speech

Community Question Answering

Understanding Language Representations in Deep Learning Models

speech and language processing

PI
Core/Dual

Berthold Horn

Professor

Vision, computational imaging

E bkph@csail.mit.edu

T 253-5863

Lead

Driver-Friendly Bilateral Control for Suppressing Traffic Instabilities

Member

EQ-Radio: Emotion Recognition using Wireless Signals

Vision, computational imaging

PI
Core/Dual

Dina Katabi

Professor

Wireless, networks, machine learning

E dina@csail.mit.edu

T 324-6027

Lead

Networks at MIT

Member

Vertical AI Community of Research

Wireless, networks, machine learning

PI
Core/Dual

Boris Katz

Principal Research Scientist

Natural language processing

E boris@csail.mit.edu

T 253-6032

Lead

Semantic Parsing using Vision

Generating Plans for Agents using Video and Language

Inferring “Theory of Mind” with vision and language

Artificial Social Intelligence for Successful Teams (ASIST)

Member

Center for Brains, Minds and Machines

Natural language processing

PI
Core/Dual

John Leonard

Professor

Robotics, navigation/mapping, self-driving cars

E jleonard@csail.mit.edu

T 253-5305

Lead

Marine Robotics Group

Member

Robotics, navigation/mapping, self-driving cars

Lucas Liebenwein

Graduate Student

Student and Researcher | Robotics, AI | Advanced Autonomy

E lucasl@mit.edu

RM 32-376C

Lead

Member

Inferring 3D Shape Distributions for Robot Perception and Planning

Student and Researcher | Robotics, AI | Advanced Autonomy

PI
Core/Dual

Nicholas Roy

Professor

Robotics, autonomy, artificial intelligence, motion planning

E nickroy@csail.mit.edu

T 253-2517

Lead

Robust Robotics Group

Member

Enabling Semantic Understanding for Autonomous Marine Robots

Robotics, autonomy, artificial intelligence, motion planning

PI
Core/Dual

Daniela Rus

Director

CSAIL director, robotics, AI, data science, privacy

E rus@csail.mit.edu

T 258-7567

RM 32/ 32-368/ 374

Lead

Social Network Extraction from GPS Datasets with Coresets

Practical Secure Computation

Soft Contact Modeling

Brain-Controlled Robots

M-Blocks Modular Robotics

Robot Compiler

Distributed Robot Garden

Route and Motion Planning for Mobility-on-Demand with Rules of the Road

Member

Social Network Extraction from GPS Datasets with Coresets

Task-Driven Co-Optimization Of Articulated Robots

Wearable Blind Navigation

Drones that Drive

Better Models for Ride-Sharing

SoFi - The Soft Robotic Fish

Controlling drones and other robots with gestures

Using Muscle Signals to Lift Objects with Robots

Helping robots learn using demonstrations

CSAIL director, robotics, AI, data science, privacy

Ryan Sander

Graduate Student

Graduate Research Assistant in MIT Distributed Robotics Laboratory

E rmsander@csail.MIT.EDU

Graduate Research Assistant in MIT Distributed Robotics Laboratory

Wilko Schwarting

Graduate Student

E wilkos@mit.edu

Lead

Member

PI
Core/Dual

Gerald Sussman

Professor

Artificial intelligence, supercomputers

E gjs@csail.mit.edu

T 253-5874

RM 32/ 32-G508/ G514

Lead

Sussman Lab

The Car Can Explain!

Member