Research

Impact Areas

Lead

Una-May O'Reilly

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

Research Group

Decentralized Information Group

We are investigating decentralized technologies that affect social change.

Lalana Kagal

Tim Berners-Lee

Leads

Lalana Kagal

Tim Berners-Lee

Research Areas

Impact Areas

Lead

Lalana Kagal

Tim Berners-Lee

Lalana Kagal

Tim Berners-Lee

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.

+13

Daniela Rus

Leads

Daniela Rus

Research Areas

Impact Areas

Lead

Daniela Rus

+13

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

Infolab

We investigate language in different contexts: from how it is learned, to how it is grounded in visual perception, all the way to how machines can readily interact with humans.

Boris Katz

Leads

Boris Katz

Research Areas

Impact Areas

Lead

Boris Katz

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

Manufacturing

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

MIT App Inventor

MIT App Inventor is an intuitive, visual programming environment that allows everyone – even children – to build fully functional apps for smartphones and tablets.

Hal Abelson

Leads

Hal Abelson

Research Areas

Impact Areas

Education

Lead

Hal Abelson

Research Group

Multicore Algorithmics

We develop techniques for designing, implementing, and reasoning about multiprocessor algorithms, in particular concurrent data structures for multicore machines and the mathematical foundations of the computation models that govern their behavior.

Nir Shavit

Leads

Nir Shavit

Research Areas

Impact Areas

Lead

Nir Shavit

Research Group

Networks at MIT

We build new protocols and architectures to improve the robustness and performance of computer networks. We develop practical solutions in wireless networks, network security, traffic engineering, congestion control, and routing.

Dina Katabi

Leads

Dina Katabi

Research Areas

Impact Areas

Wireless

Lead

Dina Katabi

Research Group

Sensing, Learning and Inference

We develop scalable algorithms for analysis of complex, high-dimensional data.

John Fisher

Leads

John Fisher

Research Areas

Impact Areas

Lead

John Fisher

Research Group

Spoken Language Systems Group

Our goal is to create technology that makes it possible for everyone in the world to interact with with computers via natural spoken language.

Jim Glass

Leads

Jim Glass

Research Areas

Impact Areas

Lead

Jim Glass

Community of Research

Systems 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

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

Eric Grimson

Berthold Horn

Aude Oliva

Antonio Torralba

Research Areas

Impact Areas

Lead

Ted Adelson

Fredo Durand

John Fisher

William Freeman

Polina Golland

Eric Grimson

Berthold Horn

Aude Oliva

Antonio Torralba

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

William Freeman

Leads

William Freeman

Research Areas

Impact Areas

Networks and Mobile Systems

Lead

William Freeman

+10

William Freeman

18 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

Computer-Aided Programming

Akshay Narayan

Francis Cangialosi

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

Spoken Language Systems Group

Daniel Jackson

Armando Solar-Lezama

Project

Automatic Speech Recognition

Automatic speech recognition (ASR) has been a grand challenge machine learning problem for decades. Our ongoing research in this area examines the use of deep learning models for distant and noisy recording conditions, multilingual, and low-resource scenarios.

Sameer Khurana

Jim Glass

Leads

Sameer Khurana

Jim Glass

Research Areas

Impact Areas

Sameer Khurana

Jim Glass

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

Decentralized Information Group

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

Gerald Sussman

Lalana Kagal

Project

CliNER: Clinical Concept Extraction

Applied Machine Learning Community of Research

Clinical concept extraction (CCE) of named entities - such as problems, tests, and treatments - aids in forming an understanding of notes and provides a foundation for many downstream clinical decision-making tasks. Historically, this task has been posed as a standard named entity recognition (NER) sequence tagging problem, and solved with feature-based methods using hand-engineered domain knowledge. Recent advances, however, have demonstrated the efficacy of LSTM-based models for NER tasks, including CCE. This work presents CliNER 2.0, a simple-to-install, open-source tool for extracting concepts from clinical text. CliNER 2.0 uses a word- and character- level LSTM model, and achieves state-of-the-art performance. For ease of use, the tool also includes pre-trained models available for public use.

Leads

William Boag

Elena Sergeeva

Peter Szolovits

Anna Rumshisky

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

Vertical AI Community of Research

Project

EQ-Radio: Emotion Recognition using Wireless Signals

Networks at MIT

EQ-Radio can infer a person’s emotions using wireless signals. It transmits an RF signal and analyzes its reflections off a person’s body to recognize his emotional state (happy, sad, etc.).

Dina Katabi

Leads

Dina Katabi

Research Areas

Impact Areas

Dina Katabi

Project

Geometry in Large-Scale Machine Learning

Machine Learning

Data often has geometric structure which can enable better inference; this project aims to scale up geometry-aware techniques for use in machine learning settings with lots of data, so that this structure may be utilized in practice.

Justin Solomon

Stefanie Jegelka

Leads

Justin Solomon

Stefanie Jegelka

Research Areas

Impact Areas

Decentralized Information Group

Justin Solomon

Stefanie Jegelka

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

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

Model-Based Embedded and Robotics Systems Group

Daniela Rus

Alexander Amini

Project

Securing IoT

IoT devices primarily use free embedded Linux which has many security flaws. We are conducting penetration tests on IoT and developing a secure version of embedded Linux.

Howard Shrobe

Leads

Howard Shrobe

Research Areas

Impact Areas

Howard Shrobe

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

Decentralized Information Group

Joseph DelPreto

Project

Solid: Social Linked Data

Solid aims to radically change the way Web applications work today, resulting in true data ownership as well as improved privacy.

Tim Berners-Lee

Lalana Kagal

Leads

Tim Berners-Lee

Lalana Kagal

Research Areas

Impact Areas

Tim Berners-Lee

Lalana Kagal

Project

Tiramisu Compiler

Commit Group

A polyhedral compiler for expressing image processing, DNN, and linear/tensor algebra applications

Saman Amarasinghe

Leads

Saman Amarasinghe

Research Areas

Computer Architecture

Impact Areas

Saman Amarasinghe

Project

Video Data Querying

Data Systems Group

We are developing machine-learning technology to help users efficiently run data queries over large archives of raw video.

Sam Madden

Favyen Bastani

Leads

Sam Madden

Favyen Bastani

Research Areas

Impact Areas

Sam Madden

Favyen Bastani

30 People Results

PI
Core/Dual

Ted Adelson

Professor

Vision, touch sensing, robotics

E adelson@csail.mit.edu

T 253-0645

Lead

Blood Pressure Imager

Member

Robust Learning for Autonomous Vehicles

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

Advanced Network Architecture Group

PhD Candidate. Autonomous vehicles. Multi-robot systems.

PI
Core/Dual

David Clark

Senior Research Scientist

Internet architectures, communications policy, security

E ddc@csail.mit.edu

T 253-6003

Lead

Internet Policy Research Initiative

Member

Systems Community of Research

Internet architectures, communications policy, security

Mustafa Doga Dogan

Graduate Student

E doga@mit.edu

Member

HCI Engineering Group

PI
Core/Dual

Fredo Durand

Professor

Vision, graphics, computational photography

E fredo@csail.mit.edu

T 253-7223

Lead

Computer Graphics Group

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

START System

Member

Infolab

PI
Core/Dual

John Fisher

Senior Research Scientist

Vision, machine learning, signal processing

E fisher@csail.mit.edu

T 253-0788

Lead

Sensing, Learning and Inference

Member

Vision, machine learning, signal processing

PI
Core/Dual

William Freeman

Professor

Vision, machine learning, Bayesian modeling

E billf@csail.mit.edu

T 253-8828

Lead

Computer Graphics Group

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

Spoken Language Systems Group

Vision, machine learning, Bayesian modeling

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

Ramin Hasani

Postdoctoral Associate

Machine learning Scientist

E rhasani@csail.mit.edu

Machine learning Scientist

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

Vision, computational imaging

PI
Core/Dual

David Karger

Professor

Helping people manage information

E karger@csail.mit.edu

T 258-6167

Lead

Haystack Group

Mavo: Creating Interactive Data-Driven Web Applications by Authoring HTML

Algorithms Group

Wikum: Bridging Discussion Systems and Wikis with Collective Summarization

Squadbox: Combating Online Harassment using Friendsourced Moderation

Eyebrowse: Social and Public Web Browsing

Talkademic: Motivating Online Academic Discourse

Member

Human-Computer Interaction Community of Research

Theory of Computation Community of Research

Systems Community of Research

Helping people manage information

PI
Core/Dual

Dina Katabi

Professor

Wireless, networks, machine learning

E dina@csail.mit.edu

T 324-6027

Lead

Networks at MIT

EQ-Radio: Emotion Recognition using Wireless Signals

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

Infolab

START System

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

Safety Standards for Autonomous Vehicles

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

Coresets for Machine Learning Algorithms

Student and Researcher | Robotics, AI | Advanced Autonomy

PI
Core/Dual

Sam Madden

Professor

Systems for processing and manipulating data

E madden@csail.mit.edu

T 258-6643

Lead

Data Systems Group

Aurum: Large Scale Data Discovery

System that Learns From IoT

Data Civilizer

Autonomous Vehicle Databases

Building a Scalable Database for Autonomous Vehicles

Chameleon: Using Machine Learning to Make Databases Faster!

Data Discovery

Systems Community of Research

Video Data Querying

Starling: Query Optimization for Cloud Services

Member

Aurum: Large Scale Data Discovery

Computation Structures Group

Systems for processing and manipulating data

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

Safety Standards for Autonomous Vehicles

Soft Contact Modeling

Practical Secure Computation

Robust Learning for Autonomous Vehicles

Brain-Controlled Robots

Planning in Congestion for Autonomous Vehicles

Socially-Compliant Behavior for Autonomous Driving

Coresets for Machine Learning Algorithms

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

Wilko Schwarting

Graduate Student

E wilkos@mit.edu

Lead

Safety Standards for Autonomous Vehicles

Planning in Congestion for Autonomous Vehicles

Socially-Compliant Behavior for Autonomous Driving

Member