Research

  • Research Areas
  • Impact Areas

Algorithms & Theory

Foundational work that includes complexity, parallel computing and game theory

AI & Machine Learning

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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8 Group Results matching all criteria

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

Ted Adelson

Durand

Fredo Durand

Fisher

John Fisher

Freeman

William Freeman

Polina Golland

Polina Golland

Grimson

Eric Grimson

Horn

Berthold Horn

oliva-headshot

Aude Oliva

Ruth Rosenholtz

Ruth Rosenholtz

Torralba

Antonio Torralba

Research Areas

AI & Machine Learning
Graphics & Vision

Impact Areas

Entertainment
Health Care
Transportation

Lead

Ted Adelson

Ted Adelson

Durand

Fredo Durand

Fisher

John Fisher

Freeman

William Freeman

Polina Golland

Polina Golland

Grimson

Eric Grimson

Horn

Berthold Horn

oliva-headshot

Aude Oliva

Ruth Rosenholtz

Ruth Rosenholtz

Torralba

Antonio Torralba

18 Project Results matching all criteria

Project

Culturally-Grounded Virtual Identities: A Case Study in a Qatari Context

Imagination, Computation, and Expression Laboratory (ICE Lab)
Mixed-methods qualitative (interviews and coding) and computational (AI) approach to understanding relationships between social identities, cultural values, and virtual identity technologies (e.g., online profiles and avatars).
Fox 1

D. Fox Harrell

Leads

Fox 1

D. Fox Harrell

Research Areas

Human-Computer Interaction

Impact Areas

Education
Entertainment
 
Fox 1

D. Fox Harrell

Project

Toward Using Virtual Identities in Computer Science Learning for Broadening Participation

Imagination, Computation, and Expression Laboratory (ICE Lab)
Our research seeks to discover best practices for using avatars to enhance performance, engagement, and STEM identity development for diverse public middle and high school computer science students. As sites of our research we run workshops in which students learn computer science in fun, relevant ways, and develop self-images as computer scientists.

Sneha Veeragoudar Harrell

Aziria Rodriguez

+1
Fox 1

D. Fox Harrell

Leads

Fox 1

D. Fox Harrell

Research Areas

AI & Machine Learning

Impact Areas

Education
Entertainment

Sneha Veeragoudar Harrell

Aziria Rodriguez

+1
 
Fox 1

D. Fox Harrell

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.

Leads

Hao Tang

Hao Tang

weining_hsu

Wei-Ning Hsu

Harwath-headshot

David Harwath

MIT CSAIL Spoken Language Systems PhD student

Sameer Khurana

Di-Chia Chueh Profile Image

Di-Chia Chueh

Jim Glass

Jim Glass

Research Areas

AI & Machine Learning
Human-Computer Interaction

Impact Areas

Big Data
Education
Entertainment
Health Care
Internet of Things

Project

Computational Knitting: Patterning and Shaping for Everyone

Computational 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.

Alexandre Kaspar

Leads

Alexandre Kaspar

Research Areas

Graphics & Vision
Human-Computer Interaction

Impact Areas

Entertainment
Manufacturing
 

Alexandre Kaspar

Project

PrivacyML - A Privacy Preserving Framework for Machine Learning

Decentralized Information Group
We are developing a general framework that enforces privacy transparently enabling different kinds of machine learning to be developed that are automatically privacy preserving.
Kagal-headshot

Lalana Kagal

Vaikkunth

Vaikkunth Mugunthan

Leads

Kagal-headshot

Lalana Kagal

Vaikkunth

Vaikkunth Mugunthan

Research Areas

AI & Machine Learning
Security & Cryptography

Impact Areas

Big Data
Cybersecurity
Education
Energy
Entertainment
Health Care
Internet of Things
Manufacturing
Transportation
 
Kagal-headshot

Lalana Kagal

Vaikkunth

Vaikkunth Mugunthan

19 News Results matching all criteria

F. Harrell
AI & Machine Learning Programming Languages & Software Engineering Education Entertainment

3Q: D. Fox Harrell on his video game for the #MeToo era

The Imagination, Computation, and Expression Laboratory at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) has released a new video game called Grayscale, which is designed to sensitize players to problems of sexism, sexual harassment, and sexual assault in the workplace.

3Q: D. Fox Harrell on his video game for the #MeToo era

bbva1
Algorithms & Theory Security & Cryptography Big Data Cybersecurity Education Entertainment Health Care Internet of Things Manufacturing

Goldwasser, Micali, and Rivest win BBVA Foundation Frontiers of Knowledge Awards

This week it was announced that MIT professors and CSAIL principal investigators Shafi Goldwasser, Silvio Micali, Ronald Rivest, and former MIT professor Adi Shamir won this year’s BBVA Foundation Frontiers of Knowledge Awards in the Information and Communication Technologies category for their work in cryptography.

Goldwasser, Micali, and Rivest win BBVA Foundation Frontiers of Knowledge Awards

PhD student Danielle Olson believes we can make digital information-sharing more natural and interpersonal, by creating immersive media to better understand each other’s feelings and backgrounds.
AI & Machine Learning Human-Computer Interaction Entertainment

Danielle Olson: Building empathy through computer science and art

Communicating through computers has become an extension of our daily reality. But as speaking via screens has become commonplace, our exchanges are losing inflection, body language, and empathy. Danielle Olson ’14, a first-year PhD student at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), believes we can make digital information-sharing more natural and interpersonal, by creating immersive media to better understand each other’s feelings and backgrounds.

Danielle Olson: Building empathy through computer science and art

System directs camera-equipped drones to maintain framing of an aerial shot.
Algorithms & Theory AI & Machine Learning Graphics & Vision Robotics Entertainment Transportation

Cinematography on the fly

In recent years, a host of Hollywood blockbusters — including “The Fast and the Furious 7,” “Jurassic World,” and “The Wolf of Wall Street” — have included aerial tracking shots provided by drone helicopters outfitted with cameras. Those shots required separate operators for the drones and the cameras, and careful planning to avoid collisions. But a team of researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and ETH Zurich hope to make drone cinematography more accessible, simple, and reliable.

Cinematography on the fly

System that learns to distinguish words’ phonemes could aid development of speech-processing systems for under-studied languages
AI & Machine Learning 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

8 Group Results

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

Ted Adelson

Durand

Fredo Durand

Fisher

John Fisher

Freeman

William Freeman

Polina Golland

Polina Golland

Grimson

Eric Grimson

Horn

Berthold Horn

oliva-headshot

Aude Oliva

Ruth Rosenholtz

Ruth Rosenholtz

Torralba

Antonio Torralba

Research Areas

AI & Machine Learning
Graphics & Vision

Impact Areas

Entertainment
Health Care
Transportation

Lead

Ted Adelson

Ted Adelson

Durand

Fredo Durand

Fisher

John Fisher

Freeman

William Freeman

Polina Golland

Polina Golland

Grimson

Eric Grimson

Horn

Berthold Horn

oliva-headshot

Aude Oliva

Ruth Rosenholtz

Ruth Rosenholtz

Torralba

Antonio Torralba

18 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.

Leads

Hao Tang

Hao Tang

weining_hsu

Wei-Ning Hsu

Harwath-headshot

David Harwath

MIT CSAIL Spoken Language Systems PhD student

Sameer Khurana

Di-Chia Chueh Profile Image

Di-Chia Chueh

Jim Glass

Jim Glass

Research Areas

AI & Machine Learning
Human-Computer Interaction

Impact Areas

Big Data
Education
Entertainment
Health Care
Internet of Things

Project

Computational Knitting: Patterning and Shaping for Everyone

Computational 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.

Alexandre Kaspar

Leads

Alexandre Kaspar

Research Areas

Graphics & Vision
Human-Computer Interaction

Impact Areas

Entertainment
Manufacturing
 

Alexandre Kaspar

Project

Culturally-Grounded Virtual Identities: A Case Study in a Qatari Context

Imagination, Computation, and Expression Laboratory (ICE Lab)
Mixed-methods qualitative (interviews and coding) and computational (AI) approach to understanding relationships between social identities, cultural values, and virtual identity technologies (e.g., online profiles and avatars).
Fox 1

D. Fox Harrell

Leads

Fox 1

D. Fox Harrell

Research Areas

Human-Computer Interaction

Impact Areas

Education
Entertainment
 
Fox 1

D. Fox Harrell

Project

PrivacyML - A Privacy Preserving Framework for Machine Learning

Decentralized Information Group
We are developing a general framework that enforces privacy transparently enabling different kinds of machine learning to be developed that are automatically privacy preserving.
Kagal-headshot

Lalana Kagal

Vaikkunth

Vaikkunth Mugunthan

Leads

Kagal-headshot

Lalana Kagal

Vaikkunth

Vaikkunth Mugunthan

Research Areas

AI & Machine Learning
Security & Cryptography

Impact Areas

Big Data
Cybersecurity
Education
Energy
Entertainment
Health Care
Internet of Things
Manufacturing
Transportation
 
Kagal-headshot

Lalana Kagal

Vaikkunth

Vaikkunth Mugunthan

Project

Toward Using Virtual Identities in Computer Science Learning for Broadening Participation

Imagination, Computation, and Expression Laboratory (ICE Lab)
Our research seeks to discover best practices for using avatars to enhance performance, engagement, and STEM identity development for diverse public middle and high school computer science students. As sites of our research we run workshops in which students learn computer science in fun, relevant ways, and develop self-images as computer scientists.

Sneha Veeragoudar Harrell

Aziria Rodriguez

+1
Fox 1

D. Fox Harrell

Leads

Fox 1

D. Fox Harrell

Research Areas

AI & Machine Learning

Impact Areas

Education
Entertainment

Sneha Veeragoudar Harrell

Aziria Rodriguez

+1
 
Fox 1

D. Fox Harrell

19 News Results

F. Harrell
AI & Machine Learning Programming Languages & Software Engineering Education Entertainment

3Q: D. Fox Harrell on his video game for the #MeToo era

The Imagination, Computation, and Expression Laboratory at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) has released a new video game called Grayscale, which is designed to sensitize players to problems of sexism, sexual harassment, and sexual assault in the workplace.

3Q: D. Fox Harrell on his video game for the #MeToo era

bbva1
Algorithms & Theory Security & Cryptography Big Data Cybersecurity Education Entertainment Health Care Internet of Things Manufacturing

Goldwasser, Micali, and Rivest win BBVA Foundation Frontiers of Knowledge Awards

This week it was announced that MIT professors and CSAIL principal investigators Shafi Goldwasser, Silvio Micali, Ronald Rivest, and former MIT professor Adi Shamir won this year’s BBVA Foundation Frontiers of Knowledge Awards in the Information and Communication Technologies category for their work in cryptography.

Goldwasser, Micali, and Rivest win BBVA Foundation Frontiers of Knowledge Awards

PhD student Danielle Olson believes we can make digital information-sharing more natural and interpersonal, by creating immersive media to better understand each other’s feelings and backgrounds.
AI & Machine Learning Human-Computer Interaction Entertainment

Danielle Olson: Building empathy through computer science and art

Communicating through computers has become an extension of our daily reality. But as speaking via screens has become commonplace, our exchanges are losing inflection, body language, and empathy. Danielle Olson ’14, a first-year PhD student at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), believes we can make digital information-sharing more natural and interpersonal, by creating immersive media to better understand each other’s feelings and backgrounds.

Danielle Olson: Building empathy through computer science and art

System directs camera-equipped drones to maintain framing of an aerial shot.
Algorithms & Theory AI & Machine Learning Graphics & Vision Robotics Entertainment Transportation

Cinematography on the fly

In recent years, a host of Hollywood blockbusters — including “The Fast and the Furious 7,” “Jurassic World,” and “The Wolf of Wall Street” — have included aerial tracking shots provided by drone helicopters outfitted with cameras. Those shots required separate operators for the drones and the cameras, and careful planning to avoid collisions. But a team of researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and ETH Zurich hope to make drone cinematography more accessible, simple, and reliable.

Cinematography on the fly

System that learns to distinguish words’ phonemes could aid development of speech-processing systems for under-studied languages
AI & Machine Learning 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