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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22 Group Results

Community of Research

Applied Machine Learning Community of Research

This CoR brings together researchers at CSAIL working across a broad swath of application domains. Within these lie novel and challenging machine learning problems serving science, social science and computer science.
Regina Barzilay
Berger
Michael Carbin
+6
Una-May O'Reilly

Una-May O'Reilly

Leads

Una-May O'Reilly

Una-May O'Reilly

Research Areas

AI & ML
Computational Biology
Programming Languages & Software Engineering

Impact Areas

Cybersecurity
Education
Health Care

Lead

Una-May O'Reilly

Una-May O'Reilly

Regina Barzilay
Berger
Michael Carbin
+6
 
Una-May O'Reilly

Una-May O'Reilly

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

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

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.
default headshot
default headshot
default headshot
+2

Leads

Weitzner

Daniel Weitzner

Abelson

Hal Abelson

Clark

David Clark

Kagal-headshot

Lalana Kagal

Karen Sollins

Karen Sollins

Gerald Sussman

Gerald Sussman

Research Areas

AI & ML
Human-Computer Interaction
Security & Cryptography

Impact Areas

Big Data
Cybersecurity
Internet of Things
Transportation

Lead

Weitzner

Daniel Weitzner

Abelson

Hal Abelson

Clark

David Clark

Kagal-headshot

Lalana Kagal

Karen Sollins

Karen Sollins

Gerald Sussman

Gerald Sussman

default headshot
default headshot
default headshot
+2

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

Theory of Computation Community of Research

The goal of the Theory of Computation CoR is to study the fundamental strengths and limits of computation as well as how these interact with mathematics, computer science, and other disciplines.
Berger
Erik Demaine
Goemans
+20
Daskalakis

Costis Daskalakis

Leads

Daskalakis

Costis Daskalakis

Research Areas

Algorithms & Theory
Computational Biology
Programming Languages & Software Engineering
Security & Cryptography

Impact Areas

Big Data
Cybersecurity

Lead

Daskalakis

Costis Daskalakis

Berger
Erik Demaine
Goemans
+20
 
Daskalakis

Costis Daskalakis

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

36 Project Results

Project

Active Learning of Models for Planning

Learning and Intelligent Systems
Machine Learning
We aim to develop a systematic framework for robots to build models of the world and to use these to make effective and safe choices of actions to take in complex scenarios.
Kaelbling

Leslie Kaelbling

Lozano-Perez

Tomas Lozano-Perez

Leads

Kaelbling

Leslie Kaelbling

Lozano-Perez

Tomas Lozano-Perez

Research Areas

Algorithms & Theory
AI & ML
Human-Computer Interaction
Robotics

Impact Areas

Big Data
Education
Entertainment
 
Kaelbling

Leslie Kaelbling

Lozano-Perez

Tomas Lozano-Perez

Project

Alloy

Software Design Group
Human-Computer Interaction Community of Research
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.
Jackson image

Daniel Jackson

Leads

Jackson image

Daniel Jackson

Research Areas

Human-Computer Interaction
Programming Languages & Software Engineering
Security & Cryptography

Impact Areas

Big Data
Cybersecurity
Education
Transportation
Wireless
 
Jackson image

Daniel Jackson

Project

Artificial Social Intelligence for Successful Teams (ASIST)

Computation Structures Group
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

Howard Shrobe

Williams

Brian Williams

Katz

Boris Katz

default headshot

Zhutian Yang

Research Areas

Computer Architecture
Human-Computer Interaction
Robotics

Impact Areas

Health Care
Transportation
Wireless

Project

Automatic Speech Recognition

Spoken Language Systems Group
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.
MIT CSAIL Spoken Language Systems PhD student

Sameer Khurana

Jim Glass

Jim Glass

Leads

MIT CSAIL Spoken Language Systems PhD student

Sameer Khurana

Jim Glass

Jim Glass

Research Areas

AI & ML
Human-Computer Interaction

Impact Areas

Big Data
Education
Entertainment
Health Care
Internet of Things
 
MIT CSAIL Spoken Language Systems PhD student

Sameer Khurana

Jim Glass

Jim Glass

Project

Determining Wikipedia's Influence on Science

Supertech Research Group
Wikipedia is one of the most widely accessed encyclopedia sites in the world, including by scientists. Our project aims to investigate just how far Wikipedia’s influence goes in shaping science.
Neil Thompson Headshot

Neil Thompson

Professor Charles E. Leiserson

Charles E. Leiserson

Leads

Neil Thompson Headshot

Neil Thompson

Professor Charles E. Leiserson

Charles E. Leiserson

Research Areas

Algorithms & Theory
Human-Computer Interaction
Programming Languages & Software Engineering

Impact Areas

Big Data
Education
 
Neil Thompson Headshot

Neil Thompson

Professor Charles E. Leiserson

Charles E. Leiserson

Project

Program Performance Prediction with Deep Learning

Programming Systems Group
Commit Group
Vertical AI Community of Research
Predicting the number of clock cycles a processor takes to execute a block of assembly instructions in steady-state (the throughput) is important for both compiler designers and performance engineers.

However, building an analytical model to do so is especially complicated in modern x86-64 Complex Instruction Set Computer (CISC) machines with sophisticated processor microarchitectures in that it is tedious, error-prone, and must be performed from scratch for each processor generation.

Ithemal is the first tool that learns to predict the throughput of a set of instructions. It does so more accurately than state-of-the-art hand-written tools currently used in compiler backends and static machine code analyzers. In particular, Ithemal has less than half the error of state-of-the-art analytical models (LLVM's llvm-mca and Intel's IACA).
default headshot
Michael Carbin
Amarasinghe

Leads

Research Areas

Programming Languages & Software Engineering

Impact Areas

Big Data
default headshot
Michael Carbin
Amarasinghe

40 People Results

R. David Edelman - Headshot

R. David Edelman

Director, Project on Technology, Economy & National Security
Machine learning, cybersecurity, governance
R. David Edelman - Headshot
T 258-6389
Machine learning, cybersecurity, governance
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.
Jim Glass

PI
Core/Dual

Jim Glass

Senior Research Scientist
speech and language processing
Jim Glass
T 253-1640
RM 32-G444

Lead

Spoken Language Systems Group
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
Embodied Intelligence Community of Research
speech and language processing
Jackson image

PI
Core/Dual

Daniel Jackson

Professor
Software design, programming, systems
Jackson image
T 258-8471
RM 32-G704

Lead

Human-Computer Interaction
Software Design Group
Rethinking Software Design
Gitless: a simple version control system built on top of Git
Déjà Vu: Constructing Apps from Concepts
Security by Design for Cyberphysical Systems
Poirot: Secure Protocol Implementation by Design
An Interlock for Self Driving Cars
Alloy
Wildcard

Member

Espalier
Human-Computer Interaction Community of Research
Systems Community of Research
Wildcard
Software design, programming, systems
Karger

PI
Core/Dual

David Karger

Professor
Helping people manage information
Karger
T 258-6167
RM 32-G592

Lead

Haystack Group
Human-Computer Interaction
Algorithms Group
Mavo: Creating Interactive Data-Driven Web Applications by Authoring HTML
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
default headshot

Henry Lieberman

Research Scientist
Henry Lieberman is a Research Scientist at MIT CSAIL, in AI and HCI.
default headshot
Henry Lieberman is a Research Scientist at MIT CSAIL, in AI and HCI.
Madden

PI
Core/Dual

Sam Madden

Professor
Systems for processing and manipulating data
Madden
T 258-6643
RM 32-G938

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

20 News Results

amar2
Algorithms & Theory Systems & Networking Health Care

Removing health-care barriers and boundaries

MIT’s Amar Gupta and his wife Poonam were on a trip to Los Angeles in 2016 when she fell and broke both wrists. She was whisked by ambulance to a reputable hospital. But staff informed the couple that they couldn’t treat her there, nor could they find another local hospital that would do so. In the end, the couple was forced to take the hospital’s stunning advice: return to Boston for treatment.

Removing health-care barriers and boundaries

Image: Shutterstock
AI & ML Systems & Networking Health Care

Using machine learning to improve patient care

Doctors are often deluged by signals from charts, test results, and other metrics to keep track of. It can be difficult to integrate and monitor all of these data for multiple patients while making real-time treatment decisions, especially when data is documented inconsistently across hospitals. In a new pair of papers, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) explore ways for computers to help doctors make better medical decisions.

Using machine learning to improve patient care

WaitSuite opens up new possibilities for "micro-learning," leveraging idle moments like when you're waiting to connect to WiFi or refresh your email.
AI & ML Human-Computer Interaction Education Internet of Things

Learn a language while you wait for WiFi

Hyper-connectivity has changed the way we communicate, wait, and productively use our time. Even in a world of 5G wireless and “instant” messaging, there are countless moments throughout the day when we’re waiting for messages, texts, and Snapchats to refresh. But our frustrations with waiting a few extra seconds for our emails to push through doesn’t mean we have to simply stand by.

Learn a language while you wait for WiFi

At the Usenix Symposium on Networked Systems Design and Implementation, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory will present a new system for allocating bandwidth in data center networks.
Systems & Networking Internet of Things Wireless

Faster page loads

A webpage today is often the sum of many different components. A user’s home page on a social-networking site, for instance, might display the latest posts from the users’ friends; the associated images, links, and comments; notifications of pending messages and comments on the user’s own posts; a list of events; a list of topics currently driving online discussions; a list of games, some of which are flagged to indicate that it’s the user’s turn; and of course the all-important ads, which the site depends on for revenues.

Faster page loads

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

MIT researchers have developed a new approach to training speech-recognition systems that doesn’t depend on transcription. Instead, their system analyzes correspondences between images and spoken descriptions of those images, as captured in a large collection of audio recordings.
AI & ML Human-Computer Interaction Big Data

Learning words from pictures

Speech recognition systems, such as those that convert speech to text on cellphones, are generally the result of machine learning. A computer pores through thousands or even millions of audio files and their transcriptions, and learns which acoustic features correspond to which typed words.But transcribing recordings is costly, time-consuming work, which has limited speech recognition to a small subset of languages spoken in wealthy nations.

Learning words from pictures

A prototype of a new speech-controlled nutrition-logging system allows users to verbally describe the contents of a meal. The system then parses the description and automatically retrieves the pertinent nutritional data.
AI & ML Human-Computer Interaction Health Care

Voice-controlled calorie counter

For people struggling with obesity, logging calorie counts and other nutritional information at every meal is a proven way to lose weight. The technique does require consistency and accuracy, however, and when it fails, it’s usually because people don't have the time to find and record all the information they need.A few years ago, a team of nutritionists from Tufts University who had been experimenting with mobile-phone apps for recording caloric intake approached members of the Spoken Language Systems Group at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), with the idea of a spoken-language application that would make meal logging even easier.

Voice-controlled calorie counter

System that learns to distinguish words’ phonemes could aid development of speech-processing systems for under-studied languages
AI & ML Human-Computer Interaction Big Data Education Entertainment Internet of Things

Learning spoken language

Every language has its own collection of phonemes, or the basic phonetic units from which spoken words are composed. Depending on how you count, English has somewhere between 35 and 45. Knowing a language’s phonemes can make it much easier for automated systems to learn to interpret speech.In the 2015 volume of Transactions of the Association for Computational Linguistics, CSAIL researchers describe a new machine-learning system that, like several systems before it, can learn to distinguish spoken words. But unlike its predecessors, it can also learn to distinguish lower-level phonetic units, such as syllables and phonemes.

Learning spoken language

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