Research

  • Impact Areas
  • Research Areas

Algorithms & Theory

Foundational work that includes complexity, parallel computing and game theory

AI & ML

Spanning natural language processing, deep-learning, computer vision and more

Computational Biology

Understanding disease via epigenomics, gene regulation and bioinformatics

Computer Architecture

How CPUs, memory and other systems are designed and organized

Graphics & Vision

Teaching computers to interpret, create and animate visual data

Human-Computer Interaction

Software and hardware that let us naturally interact with technology

Programming Languages & Software Engineering

From compilers and verification to software design and engineering

Robotics

Vision, actuation, sensing and manipulation of machines

Security & Cryptography

Developing technologies to prevent and recover from cyber-attacks

Systems & Networking

From distributed systems and databases to wireless

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17 Group Results

Research Center

Center for Deployable Machine Learning (CDML)

The MIT Center for Deployable Machine Learning (CDML) works towards creating AI systems that are robust, reliable and safe for real-world deployment.
Daskalakis
Moitra-headshot
Rinard
+5
Madry-headshot

Aleksander Madry

Leads

Madry-headshot

Aleksander Madry

Research Areas

Algorithms & Theory
AI & ML
Graphics & Vision
Human-Computer Interaction
Programming Languages & Software Engineering
Robotics
Security & Cryptography

Impact Areas

Big Data
Cybersecurity

Lead

Madry-headshot

Aleksander Madry

Daskalakis
Moitra-headshot
Rinard
+5
 
Madry-headshot

Aleksander Madry

Community of Research

Cognitive AI Community of Research

This CoR aims to develop AI technology that synthesizes symbolic reasoning, probabilistic reasoning for dealing with uncertainty in the world, and statistical methods for extracting and exploiting regularities in the world, into an integrated picture of intelligence that is informed by computational insights and by cognitive science.
Brewer-headshot
Randall Davis
Kagal-headshot
+6
Howard Shrobe

Howard Shrobe

Leads

Howard Shrobe

Howard Shrobe

Research Areas

Human-Computer Interaction
Robotics
Security & Cryptography
Systems & Networking

Impact Areas

Cybersecurity
Education

Lead

Howard Shrobe

Howard Shrobe

Brewer-headshot
Randall Davis
Kagal-headshot
+6
 
Howard Shrobe

Howard Shrobe

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.
Abelson
Berners-Lee
Brewer-headshot
+8
Weitzner

Daniel Weitzner

Leads

Weitzner

Daniel Weitzner

Research Areas

Algorithms & Theory
AI & ML
Human-Computer Interaction
Security & Cryptography
Systems & Networking

Impact Areas

Big Data
Cybersecurity
Health Care
Internet of Things
Transportation
Wireless

Lead

Weitzner

Daniel Weitzner

Abelson
Berners-Lee
Brewer-headshot
+8
 
Weitzner

Daniel Weitzner

Community of Research

Human-Computer Interaction Community of Research

The focus of the HCI CoR is inventing new systems and technology that lie at the interface between people and computation, and understanding their design, implementation, and societal impact.
Randall Davis
Fox 1
Jackson image
+4
Stefanie Mueller

Stefanie Mueller

Leads

Stefanie Mueller

Stefanie Mueller

Research Areas

Graphics & Vision
Human-Computer Interaction
Programming Languages & Software Engineering

Impact Areas

Education
Entertainment
Manufacturing

Lead

Stefanie Mueller

Stefanie Mueller

Randall Davis
Fox 1
Jackson image
+4
 
Stefanie Mueller

Stefanie Mueller

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.
Alizadeh-headshot
Arvind
Hari Balakrishnan
+21
Madden

Sam Madden

Leads

Madden

Sam Madden

Research Areas

Computer Architecture
Programming Languages & Software Engineering
Security & Cryptography
Systems & Networking

Impact Areas

Big Data
Cybersecurity
Internet of Things
Transportation
Wireless

Lead

Madden

Sam Madden

Alizadeh-headshot
Arvind
Hari Balakrishnan
+21
 
Madden

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.
Amarasinghe
Regina Barzilay
Broderick-headshot
+7
Rinard

Martin Rinard

Leads

Rinard

Martin Rinard

Research Areas

Algorithms & Theory
AI & ML
Graphics & Vision
Programming Languages & Software Engineering
Security & Cryptography
Systems & Networking

Impact Areas

Big Data
Cybersecurity
Health Care
Internet of Things
Transportation
Wireless

Lead

Rinard

Martin Rinard

Amarasinghe
Regina Barzilay
Broderick-headshot
+7
 
Rinard

Martin Rinard

17 Project Results

Project

Computational Knitting: Patterning and Shaping for Everyone

Computational Design and Fabrication Group
Knitting is the new 3d printing. It has become popular again with the widespread availability of patterns and templates, together with the maker movements. Lower-cost industrial knitting machines are starting to emerge, but we are still missing the corresponding design tools. Our goal is to fill this gap.
default headshot

Alexandre Kaspar

Leads

default headshot

Alexandre Kaspar

Research Areas

Graphics & Vision
Human-Computer Interaction

Impact Areas

Entertainment
Manufacturing
 
default headshot

Alexandre Kaspar

Project

Denial of Service Mitigation through Protocol Design

Advanced Network Architecture Group
Computing & Society Community of Research
We aim to better understand the features of network protocols that facilitate denial of service attacks, in order to design more robust protocols and architectures in the future and evaluate existing designs more accurately.
Karen Sollins

Karen Sollins

Leads

Karen Sollins

Karen Sollins

Research Areas

Security & Cryptography
Systems & Networking

Impact Areas

Cybersecurity
 
Karen Sollins

Karen Sollins

Project

Solid: Social Linked Data

Decentralized Information Group
Cognitive AI Community of Research
Computing & Society Community of Research
Solid aims to radically change the way Web applications work today, resulting in true data ownership as well as improved privacy.
default headshot
Berners-Lee

Tim Berners-Lee

Kagal-headshot

Lalana Kagal

Leads

Berners-Lee

Tim Berners-Lee

Kagal-headshot

Lalana Kagal

Research Areas

Programming Languages & Software Engineering
Systems & Networking

Impact Areas

Cybersecurity
Health Care
Internet of Things
default headshot
 
Berners-Lee

Tim Berners-Lee

Kagal-headshot

Lalana Kagal

28 People Results

Chlipala-headshot

PI
Core/Dual

Adam Chlipala

Associate Professor
Programming languages, formal methods, security & privacy, systems
Chlipala-headshot
T 324-8439
RM 32-G842

Lead

Kami: A Modular Deductive Hardware Verification Platform
Compilation Using Correct-by-Construction Program Synthesis
Programming Languages & Verification
Hemiola: Structural Design and Proof of Cache-Coherence Protocols

Member

Compilation Using Correct-by-Construction Program Synthesis
Programming with spaces
Computation Structures Group
FSCQ: File-system verification
Systems Community of Research
Programming languages, formal methods, security & privacy, systems
Gregory Falco

Gregory Falco

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

Michael Foshey

Mechanical Engineer/Project Manager
Additive Manufacturing, Robotics, Digital Fabrication
...
RM 32-321
Additive Manufacturing, Robotics, Digital Fabrication
Kaelbling

PI
Core/Dual

Leslie Kaelbling

Professor
Robotics, machine learning, motion planning
Kaelbling
T 258-9695
RM 32-333

Lead

Learning and Intelligent Systems
Machine Learning
Learning and Optimization
Robotic Planning and Manipulation with Force Information
Reliable Robotic Construction of Multi-object Arrangements
Learning and Planning with Compressed Linear Expectation Models
Active Learning of Models for Planning
Task and Motion Planning for Autonomous Robots
Robust Intelligent Robots
Embodied Intelligence Community of Research

Member

Robust Intelligent Robots
Robotics, machine learning, motion planning
Lozano-Perez

PI
Core/Dual

Tomas Lozano-Perez

Professor
Robotics, artificial intelligence
Lozano-Perez
T 253-7889
RM 32-333

Lead

Learning and Intelligent Systems
Learning and Optimization
Robotic Planning and Manipulation with Force Information
Reliable Robotic Construction of Multi-object Arrangements
Learning and Planning with Compressed Linear Expectation Models
Active Learning of Models for Planning
Task and Motion Planning for Autonomous Robots
Robust Intelligent Robots

Member

Robust Intelligent Robots
Embodied Intelligence Community of Research
Robotics, artificial intelligence
Rus

PI
Core/Dual

Daniela Rus

Director
CSAIL director, robotics, AI, data science, privacy
Rus
T 258-7567
RM 32/ 32-368/ 374

Lead

Distributed Robotics Laboratory
Social Network Extraction from GPS Datasets with Coresets
Safety Standards for Autonomous Vehicles
Soft Contact Modeling
Practical Secure Computation
Self-Driving Vehicles
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
Embodied Intelligence Community of Research
Helping robots learn using demonstrations
CSAIL director, robotics, AI, data science, privacy
solomon-headshot

PI
Core/Dual

Justin Solomon

Assistant Professor
Geometry, graphics, vision, machine learning, optimization.
solomon-headshot
RM 32-D460

Lead

Computer Graphics Group
Geometric Data Processing Group
Geometry in Large-Scale Machine Learning
Political Geometry: Establishing Fair Mathematical Standards for Political Redistricting
Sensible Deep Learning for 3D Data
Optimal transport for statistics and machine learning
Geometry and topology for scientific computing and shape analysis

Member

Visual Computing Community of Research
Geometry, graphics, vision, machine learning, optimization.

13 News Results

Formally verified working file system could lead to computers guaranteed never to lose your data.
Security & Cryptography Systems & Networking Cybersecurity

Crash-proof computer systems

In a computer operating system, the file system is the part that writes data to disk and tracks where the data is stored. If the computer crashes while it’s writing data, the file system’s records can become corrupt. Hours of work could be lost, or programs could stop working properly.At a symposium this fall, MIT researchers will present the first file system that is mathematically guaranteed not to lose track of data during crashes. Although the file system is slow by today’s standards, the techniques the researchers used to verify its performance can be extended to more sophisticated designs. Ultimately, formal verification could make it much easier to develop reliable, efficient file systems.

Crash-proof computer systems

Image: Jose-Luis Olivares
Algorithms & Theory AI & ML Systems & Networking Big Data Energy

What better wind-speed prediction can do for the energy industry

When a power company wants to build a new wind farm, it generally hires a consultant to make wind speed measurements at the proposed site for eight to 12 months. Those measurements are correlated with historical data and used to assess the site’s power-generation capacity.This month CSAIL researchers will present a new statistical technique that yields better wind-speed predictions than existing techniques do — even when it uses only three months’ worth of data. That could save power companies time and money, particularly in the evaluation of sites for offshore wind farms, where maintaining measurement stations is particularly costly.

What better wind-speed prediction can do for the energy industry