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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7 Group Results

Research Group

Algorithms Group

We devise new mathematical tools to tackle the increasing difficulty and importance of problems we pose to computers.

Leads

Daskalakis

Costis Daskalakis

Erik Demaine

Erik Demaine

Goemans

Michael Goemans

Indyk

Piotr Indyk

Karger

David Karger

Jonathan Kelner

Jonathan Kelner

Leighton

Tom Leighton

Professor Charles E. Leiserson

Charles E. Leiserson

Madry-headshot

Aleksander Madry

Moitra-headshot

Ankur Moitra

Rubinfeld

Ronitt Rubinfeld

shavit-headshot

Nir Shavit

RWilliams-headshot

Ryan Williams

VWilliams-headshot

Virginia Vassilevska Williams

Research Areas

Algorithms & Theory

Impact Areas

Big Data
Cybersecurity
Energy
Wireless

Lead

Daskalakis

Costis Daskalakis

Erik Demaine

Erik Demaine

Goemans

Michael Goemans

Indyk

Piotr Indyk

Karger

David Karger

Jonathan Kelner

Jonathan Kelner

Leighton

Tom Leighton

Professor Charles E. Leiserson

Charles E. Leiserson

Madry-headshot

Aleksander Madry

Moitra-headshot

Ankur Moitra

Rubinfeld

Ronitt Rubinfeld

shavit-headshot

Nir Shavit

RWilliams-headshot

Ryan Williams

VWilliams-headshot

Virginia Vassilevska Williams

7 Project Results

4 People Results

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

11 News Results

Researchers at MIT’s Microsystems Technology Laboratories have built a low-power chip specialized for automatic speech recognition. With power savings of 90 to 99 percent, it could make voice control practical for relatively simple electronic devices.
AI & ML Human-Computer Interaction Energy Internet of Things Manufacturing

Voice control everywhere

The butt of jokes as little as 10 years ago, automatic speech recognition is now on the verge of becoming people’s chief means of interacting with their principal computing devices. In anticipation of the age of voice-controlled electronics, MIT researchers have built a low-power chip specialized for automatic speech recognition. Whereas a cellphone running speech-recognition software might require about 1 watt of power, the new chip requires between 0.2 and 10 milliwatts, depending on the number of words it has to recognize.

Voice control everywhere

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