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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1 Group Results matching all criteria

2 People Results matching all criteria

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.

1 News Results matching all criteria

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

30 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

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

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.
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default headshot
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+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

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default headshot
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+2

40 Project Results

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

CliNER: Clinical Concept Extraction

Cognitive AI Community of Research
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

Willie

William Boag

Elena Sergeeva

Elena Sergeeva

Szolovits

Peter Szolovits

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Anna Rumshisky

Research Areas

AI & ML

Impact Areas

Energy

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.
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Alexandre Kaspar

Leads

default headshot

Alexandre Kaspar

Research Areas

Graphics & Vision
Human-Computer Interaction

Impact Areas

Entertainment
Manufacturing
 
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Alexandre Kaspar

38 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
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
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

Member

Robust Intelligent Robots
Embodied Intelligence Community of Research
Robotics, machine learning, motion planning
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
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
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

52 News Results

CSAIL1
Algorithms & Theory Computer Architecture Big Data Cybersecurity Health Care Internet of Things Manufacturing

MIT hosts workshop on theoretical foundations of deep learning

Last week MIT’s Institute for Foundations of Data Science (MIFODS) held an interdisciplinary workshop aimed at tackling the underlying theory behind deep learning. Led by MIT professor Aleksander Madry, the event focused on a number of research discussions at the intersection of math, statistics, and theoretical computer science.

MIT hosts workshop on theoretical foundations of deep learning