Research

Impact Areas

Lead

Una-May O'Reilly

Research Group

Center for Brains, Minds and Machines

Our main goal is developing a computationally based understanding of human intelligence and establishing an engineering practice based on that understanding.

Tomaso Poggio

Leads

Tomaso Poggio

Research Areas

Impact Areas

Lead

Tomaso Poggio

Research Group

Clinical Decision-Making Group

We focus on furthering the application of technology and artificial intelligence in medicine and health-care.

+11

Peter Szolovits

Leads

Peter Szolovits

Research Areas

Impact Areas

Lead

Peter Szolovits

+11

Peter Szolovits

Research Group

Clinical Machine Learning Group

Our group is interested in using machine learning and artificial intelligence to transform health care.

David Sontag

Leads

David Sontag

Research Areas

Impact Areas

Lead

David Sontag

Research Group

Computational Biology Group

We seek to understand the mechanistic basis of human disease, using a combination of computational and experimental techniques.

Manolis Kellis

Leads

Manolis Kellis

Research Areas

Impact Areas

Lead

Manolis Kellis

Research Group

Computational Cognitive Science Group

We study the computational basis of human learning and inference.

Joshua Tenenbaum

Leads

Joshua Tenenbaum

Research Areas

Impact Areas

Lead

Joshua Tenenbaum

Research Group

Computational Fabrication Group

Our research centers on digital manufacturing, 3D printing and computer graphics, as well as computational photography and displays, and virtual humans and robotics.

Wojciech Matusik

Leads

Wojciech Matusik

Research Areas

Impact Areas

Lead

Wojciech Matusik

Research Group

Computational Genomics Group

We develop new machine learning techniques and algorithms to model the transcriptional regulatory networks that control gene expression programs in living cells.

Dave Gifford

Leads

Dave Gifford

Research Areas

Impact Areas

Lead

Dave Gifford

Research Group

Computational Perception & Cognition

We combine methods from computer science, neuroscience and cognitive science to explain and model how perception and cognition are realized in human and machine.

Aude Oliva

Leads

Aude Oliva

Research Areas

Impact Areas

Lead

Aude Oliva

Research Group

Computer Graphics Group

Our group focuses on synthetic image generation and computational photography.

+20

Leads

Fredo Durand

William Freeman

Wojciech Matusik

Justin Solomon

Research Areas

Impact Areas

Lead

Fredo Durand

William Freeman

Wojciech Matusik

Justin Solomon

+20

Research Group

Data-Driven Inference Group

We use machine learning and computer vision to improve outcomes in medicine, finance, and sports

John Guttag

Leads

John Guttag

Research Areas

Impact Areas

Lead

John Guttag

Research Group

Decentralized Information Group

We are investigating decentralized technologies that affect social change.

Lalana Kagal

Tim Berners-Lee

Leads

Lalana Kagal

Tim Berners-Lee

Research Areas

Impact Areas

Lead

Lalana Kagal

Tim Berners-Lee

Lalana Kagal

Tim Berners-Lee

Research Group

Distributed Robotics Laboratory

We aim to develop the science of autonomy toward a future with robots and AI systems integrated into everyday life, supporting people with cognitive and physical tasks.

+19

Daniela Rus

Leads

Daniela Rus

Research Areas

Impact Areas

Lead

Daniela Rus

+19

Daniela Rus

Research Group

Genesis Group

The Genesis Group focuses on developing an account of human intelligence with special
emphasis on developing computational models of how people tell, perceive and understand
stories.

Leads

Research Areas

Impact Areas

Research Group

Haystack Group

We are an interdisciplinary group of researchers blending approaches from human-computer interaction, social computing, databases, information management, and databases.

Lea Verou

David Karger

Leads

David Karger

Research Areas

Impact Areas

Internet of Things

Lead

David Karger

Lea Verou

David Karger

Research Group

HCI Engineering Group

We work at the intersection of human computer interaction and personal fabrication tools.

Stefanie Mueller

Leads

Stefanie Mueller

Research Areas

Impact Areas

Lead

Stefanie Mueller

Research Group

Randall Davis

Fredo Durand

Daniel Jackson

David Karger

Rob Miller

Stefanie Mueller

Research Areas

Lead

Randall Davis

Fredo Durand

Daniel Jackson

David Karger

Rob Miller

Stefanie Mueller

Research Group

Imagination, Computation, and Expression Laboratory (ICE Lab)

We develop computing systems for creative expression, cultural analysis, and social change.

Peter Mawhorter

D. Fox Harrell

Leads

D. Fox Harrell

Research Areas

Impact Areas

Lead

D. Fox Harrell

Peter Mawhorter

D. Fox Harrell

Research Group

Interactive Robotics Group

The Interactive Robotics Group aims to imagine the future of work by designing collaborative robot teammates that enhance human capability.

Julie Shah

Leads

Julie Shah

Research Areas

Impact Areas

Lead

Julie Shah

Research Group

Infolab

We investigate language in different contexts: from how it is learned, to how it is grounded in visual perception, all the way to how machines can readily interact with humans.

Boris Katz

Leads

Boris Katz

Research Areas

Impact Areas

Lead

Boris Katz

Research Group

Learning and Intelligent Systems

We conduct interdisciplinary research aimed at discovering the principles underlying the design of artificially intelligent robots.

Leslie Kaelbling

Tomas Lozano-Perez

Leads

Leslie Kaelbling

Tomas Lozano-Perez

Research Areas

Impact Areas

Lead

Leslie Kaelbling

Tomas Lozano-Perez

Leslie Kaelbling

Tomas Lozano-Perez

Research Group

Machine Learning

We work on a variety of topics spanning theoretical foundations, algorithms, and applications.

Leads

Tamara Broderick

Tommi Jaakkola

Stefanie Jegelka

Leslie Kaelbling

David Sontag

Research Areas

Impact Areas

Lead

Tamara Broderick

Tommi Jaakkola

Stefanie Jegelka

Leslie Kaelbling

David Sontag

Research Group

Marine Robotics Group

Our projects are centered around the problems of navigation and mapping for autonomous mobile robots operating in underwater and terrestrial environments.

John Leonard

Leads

John Leonard

Research Areas

Impact Areas

Energy

Lead

John Leonard

Research Group

Medical Vision Group

We develop new algorithms for medical image analysis and visualization of medical imagery.

+12

Polina Golland

Leads

Polina Golland

Research Areas

Impact Areas

Lead

Polina Golland

+12

Polina Golland

289 Project Results matching all criteria

Project

Squadbox: Combating Online Harassment using Friendsourced Moderation

Haystack Group

Fight back against online harassment with a squad of friends.

Amy Zhang

David Karger

Leads

Amy Zhang

David Karger

Research Areas

Amy Zhang

David Karger

Project

Inferring 3D Shape Distributions for Robot Perception and Planning

Robust Robotics Group

Our goal is to develop methods for a mobile robot to reason about volumetric spatial uncertainty of objects in its environment.

Nicholas Roy

Leads

Nicholas Roy

Research Areas

Impact Areas

Nicholas Roy

Project

Synquid: Synthesis From Liquid Types

Type-driven program synthesis

Armando Solar-Lezama

Leads

Armando Solar-Lezama

Research Areas

Armando Solar-Lezama

Project

Deep Inverse Planning

Deep inverse planning for learning from high-dimensional demonstrations

Leads

Research Areas

Imagination, Computation, and Expression Laboratory (ICE Lab)

Project

Developing the Impacts of Virtual Identity on Computational Learning Environments

Our goal is to develop an understanding of the impacts of virtual identities on users in educational environments.

D. Fox Harrell

Leads

D. Fox Harrell

Research Areas

Computational Cognitive Science Group

D. Fox Harrell

Project

Beating the World's Best at Super Smash Bros. with Deep Reinforcement Learning

We use deep reinforcement learning and self-play to train human-level agents for a multiplayer fighting game.

Leads

Project

Wait-learning: Intelligent Systems for Making Productive Use of Wait Time

Usable Programming Group

Wait-learning makes it easier for busy people to learn informally, by automatically detecting when they are waiting and delivering optional learning exercises that can be completed during wait time.

Rob Miller

Leads

Rob Miller

Research Areas

Impact Areas

Rob Miller

Project

Monitoring Fetal Health

We develop algorithms for fetal MRI interpretation, to enable noninvasive fetal monitoring from MRI.

Polina Golland

Leads

Polina Golland

Research Areas

Impact Areas

Computational Fabrication Group

Polina Golland

Project

Scalable Bayesian Inference via Adaptive Data Summaries

Machine Learning

To obtain scalable Bayesian inference methods, we develop algorithms to create compact “summaries” of large quantities of data. We can then quickly run standard inference algorithms on these summaries without needing to look at the whole dataset.

Jonathan Huggins

Tamara Broderick

Leads

Jonathan Huggins

Tamara Broderick

Jonathan Huggins

Tamara Broderick

Project

3D-Printed Organic Solar Cells

Using our inkjet printer system, the goal of this project is to produce a light sensor / solar cell that is composed entirely of 3D printed materials.

James Minor

Leads

James Minor

Research Areas

Impact Areas

James Minor

Project

Learning the Arrow of Time from Videos

We train machines to visually detect the arrow of time, if a video is playing forward or backward, by watching millions of online clips.

Leads

Research Areas

Project

Computational Multicopter Design

A system that can help you to design our own drone!

Tao Du

Leads

Tao Du

Research Areas

Impact Areas

Energy

Tao Du

Project

Understanding Light via Deep Neural Networks

Our goal is to understand the illumination of an environment. By disentangling the illumination effect from other intrinsic properties (e.g. geometry, texture, color), we can better understand how human perceive the world. It also has several applications such as single image relighting, color editing, etc.

Wei-Chiu Ma

Antonio Torralba

Leads

Wei-Chiu Ma

Antonio Torralba

Research Areas

Wei-Chiu Ma

Antonio Torralba

Project

Multi-Core Data Structures

Multicore Algorithmics

We aim to develop data structures optimized for large-scale multi-core computers.

Nir Shavit

Leads

Nir Shavit

Research Areas

Nir Shavit

Project

Characterizing the Sensitivity of Vision-in-the-Loop Driving Controllers Using CG

We work on understanding and improving vision algorithms used for self driving cars, by introducing synthetic data-sets to the loop.

Leads

Research Areas

Impact Areas

Center for Brains, Minds and Machines

Project

Orbit Metric Learning: Weak Supervision for Invariant Representations

Visual recognition is affected by changes in visual appearance (pose, scale, rotation) that do not affect a scene’s semantic category. We introduce a method for using sets of traNational Science Foundationorming examples, to learn representations that are robust to these changes.

Leads

Research Areas

Center for Brains, Minds and Machines

Project

Spatio-temporal Convolutional Networks Explain Neural Representations of Human Action

Spatio-temporal convolutional networks are a good model of how visual cortex represents the actions of others, and thinking about robustness to complex transformations, is key to uncovering how human visual cortex is organized.

Leads

Research Areas

Project

3D Generative Adversarial Networks

We study the problem of 3D object generation. We propose a novel framework, 3D Generative Adversarial Network (3D-GAN), leveraging recent advances in volumetric convolutional networks and generative adversarial nets.

Jiajun Wu

Leads

Jiajun Wu

Research Areas

Impact Areas

Parallel and Distributed Operating Systems

Jiajun Wu

Project

FSCQ: File-system verification

FSCQ is the first file system with a machine-checkable proof (in the Coq proof assistant) that its implementation meets its specification and whose specification includes behavior under crashes.

Tej Chajed

Leads

Tej Chajed

Research Areas

Computational Fabrication Group

Tej Chajed

Project

Crowdsourcing in Graphics and Vision

Our goal is to develop new applications and algorithms that leverage the skills of distributed crowdworkers, notably for image and video processing applications.

Alexandre Kaspar

Leads

Alexandre Kaspar

Research Areas

Impact Areas

Alexandre Kaspar

Project

Learning Optimal Interventions

Machine Learning

We develop statistical models that are prescriptive rather than predictive/descriptive. From an observational dataset, our methods learn to automatically identify beneficial actions that will improve outcomes, rather than requiring human-made decisions.

Jonas Mueller

Leads

Jonas Mueller

Project

Peripheral Vision and Driver Behavior

Our goal is to understand what drivers can perceive when they are not attending to the road ahead and the consequences of their perceptions for safety.

Leads

Research Areas

Impact Areas

Networks and Mobile Systems

Project

Neural Adaptive Bitrate Streaming using Reinforcement Learning

Reinforcement Learning and Neural Networks are used for boosting bitrate adaptation performance in video streaming, which outperforms state-of-the-arts algorithms by 13.1% - 25.0%.

Hongzi Mao

Leads

Hongzi Mao

Research Areas

Theory of Distributed Systems Group

Hongzi Mao

Project

Distributed Computation in Ant Colonies

We are interested in applying insights from distributed computing theory to understand how ants and other social insects work together to perform complex tasks such as foraging for food, allocating tasks to workers, and choosing high quality nest sites.

Nancy Lynch

Leads

Nancy Lynch

Research Areas

Internet Policy Research Initiative

Nancy Lynch

1530 People Results matching all criteria

Scott Aaronson

Visiting Professor

E aaronson@csail.mit.edu

T 324-8356

Nezar Abdennur

Graduate Student

E nezar@MIT.EDU

Zachary Abel

Temporary Lecturer

E zabel@mit.edu

PI
Core/Dual

Hal Abelson

Professor

Programming, privacy, App Inventor

E hal@mit.edu

T 253-5856

Lead

MIT App Inventor

Member

Keys Under Doormats

Keeping America Safe: Toward More Secure Networks for Critical Sectors

Programming, privacy, App Inventor

Maleen Abeydeera

Graduate Student

E maleen@csail.mit.edu

Member

Pervasive Parallelism with the Swarm Architecture

Madeline Abrahams

Super UROP

Murad Abu-Khalaf

Program Manager, Toyota-CSAIL Joint Research Center

E murad@mit.edu

T 452-2859

Grace Abuhamad

Graduate Student

E abuhamad@mit.edu

Mazdak Abulnaga

Graduate Student

medical vision

E abulnaga@mit.edu

Member

Monitoring Fetal Health

medical vision

Sara Achour

Graduate Student

E sachour@mit.edu

Hannah Adams

UROP

E hadams@mit.edu

Ravichandra Addanki

Graduate Student

E addanki@mit.edu

Julius Adebayo

Graduate Student

E juliusad@MIT.EDU

RM 32-G528B

PI
Core/Dual

Ted Adelson

Professor

Vision, touch sensing, robotics

E adelson@csail.mit.edu

T 253-0645

Lead

Blood Pressure Imager

Member

Vision, touch sensing, robotics

Aviv Adler

Graduate Student

E adlera@mit.edu

Iman Aganj

Research Affiliate

E iman@csail.mit.edu

Anant Agarwal

Professor

Systems, architecture, online learning, edX

E agarwal@edx.org

T 253-1448

Systems, architecture, online learning, edX

Raj Agrawal

Graduate Student

E rajisme@mit.edu

Monica Agrawal

Graduate Student

E magrawal@mit.edu

PI
Core/Dual

Pulkit Agrawal

Assistant Professor

Reinforcement Learning, Computer Vision, Learning for Control

E PULKITAG@CSAIL.MIT.EDU

RM 32-386D

Reinforcement Learning, Computer Vision, Learning for Control

Leandro Agudelo

Postdoctoral Associate

Computational Biology, Integrative Systems Biology

E lagudelo@csail.mit.edu

Computational Biology, Integrative Systems Biology

Wajeeha Ahmad

Graduate Student

E wajeeha@mit.edu

Peter Ahrens

Graduate Student

E pahrens@mit.edu

Amanda Ahteck

UROP

E asahteck@mit.edu

1490 News Results matching all criteria

December 04 '19

Hari Balakrishnan named 2020 IEEE Fellow

The professor was elected for his contributions to the design and application of mobile sensing systems.

Hari Balakrishnan named 2020 IEEE Fellow

November 27 '19

Producing better guides for medical-image analysis

Model quickly generates brain scan templates that represent a given patient population.

Producing better guides for medical-image analysis

Security & Cryptography

November 22 '19

Daniel Weitzner named National Academy of Public Administration 2019 Fellow

November 22 '19

MIT AI conference aims to prepare workers for the jobs of the future

As automation rises in the workplace, speakers explore ways to train students and reskill workers.

MIT AI conference aims to prepare workers for the jobs of the future

MIT-invented model efficiently and simultaneously optimizes control and design of soft robots for target tasks,

November 21 '19

How to design and control robots with stretchy, flexible bodies

Optimizing soft robots to perform specific tasks is a huge computational problem, but a new model can help.

How to design and control robots with stretchy, flexible bodies

November 19 '19

Bot beats humans in hidden-identity games

Using deductive reasoning, the bot identifies friend or foe to ensure victory over humans in certain online games.

Bot beats humans in hidden-identity games

November 18 '19

Predicting people's driving personalities

New system sizes up drivers as selfish or selfless. Could this help self-driving cars navigate in traffic?

Predicting people's driving personalities

Algorithms & Theory AI & Machine Learning Robotics

November 13 '19

Autonomous system improves environmental sampling at sea

Robotic boats could more rapidly locate the most valuable sampling spots in uncharted waters.

Autonomous system improves environmental sampling at sea

November 04 '19

Better autonomous “reasoning” at tricky intersections

CSAIL/Toyota model alerts driverless cars when it’s safest to merge into traffic at intersections with obstructed views.

Better autonomous “reasoning” at tricky intersections

November 01 '19

William Freeman wins ICCV career award

Freeman was honored for his contributions to the field of computer vision

William Freeman wins ICCV career award

AI & Machine Learning Robotics Manufacturing Transportation

October 30 '19

Self-transforming robot blocks jump, spin, flip, and identify each other

Developed at MIT’s Computer Science and Artificial Intelligence Laboratory, a team of robots can self-assemble to form different structures with applications in inspection, disaster response, and manufacturing

Self-transforming robot blocks jump, spin, flip, and identify each other

Algorithms & Theory AI & Machine Learning

October 29 '19

Pushy robots learn the fundamentals of object manipulation

Systems “learn” from novel dataset that captures how pushed objects move, to improve their physical interactions with new objects.

Pushy robots learn the fundamentals of object manipulation

Algorithms & Theory AI & Machine Learning Robotics

October 29 '19

Deep learning with point clouds

Research aims to make it easier for self-driving cars, robotics, and other applications to understand the 3D world.

Deep learning with point clouds

Algorithms & Theory Health Care

October 29 '19

Recovering “lost dimensions” of images and video

Model could recreate video from motion-blurred images and “corner cameras,” may someday retrieve 3D data from 2D medical images.

Recovering “lost dimensions” of images and video

October 27 '19

Helping self-driving cars see around corners

By sensing tiny changes in shadows, CSAIL's new system identifies approaching objects that may cause a collision

Helping self-driving cars see around corners

AI & Machine Learning

October 24 '19

Better fact-checking for fake news

New research reveals biases in fake news datasets and improves the use of automatic detectors.

Better fact-checking for fake news

October 16 '19

Domain Specific Architectures for Deep Neural Networks: Three Generations of Tensor Processing Units (TPUs)

On October 16, 2019, Prof. David Patterson, UC Berkeley professor emeritus, Google distinguished engineer, and RISC-V Foundation vice-chair, gave a Dertouzos Distinguished Lecture at CSAIL / MIT, entitled 'Domain Specific Architectures for Deep Neural Networks: Three Generations of Tensor Processing Units (TPUs).'

Domain Specific Architectures for Deep Neural Networks: Three Generations of Tensor Processing Units (TPUs)

David Clark, Cecilia Testart and Philipp Richter

October 09 '19

Using machine learning to hunt down cybercriminals

CSAIL model identifies “serial hijackers” of internet IP addresses.

Using machine learning to hunt down cybercriminals

Programming Languages & Software Engineering

October 02 '19

Alan Edelman of MIT Recognized with Prestigious 2019 IEEE Computer Society Sidney Fernbach Award

Alan Edelman, professor of applied mathematics at MIT, has been selected to receive the 2019 IEEE Computer Society Sidney Fernbach Award.

Alan Edelman of MIT Recognized with Prestigious 2019 IEEE Computer Society Sidney Fernbach Award

October 02 '19

Better fetal health - by building a map of the placenta

New technique stretches out MRI scans of placentas so they can be more accurately analyzed, and shows the potential of MRI for pregnancy monitoring.

Better fetal health - by building a map of the placenta

An MIT-invented algorithm automatically produces a “portamento” effect — a pitch sliding from one note to another — between any two audio signals in real time. The algorithm finds the optimal way to move pitches from one signal into another to produce a smooth transition between sounds (shown here).

September 27 '19

Using math to blend musical notes seamlessly

Algorithm enables one audio signal to glide into another, recreating the “portamento” effect of some musical instruments.

Using math to blend musical notes seamlessly

Computational Biology

September 25 '19

Josh Tenenbaum receives 2019 MacArthur Fellowship

Brain and cognitive sciences professor studies how the human mind is able to learn so rapidly.

Josh Tenenbaum receives 2019 MacArthur Fellowship

photo of Yoshua Bengio, credit Maryse Boyce

September 18 '19

Learning High-Level Representations for Agents

Septmeber 18, 2019 - Prof. Yoshua Bengio, Prof. University of Montreal, and Scientific Director, Mila, gave a Dertouzos Distinguished Lecture at CSAIL entitled 'Learning High-Level Representations for Agents'

Learning High-Level Representations for Agents

September 12 '19

How hardware wallets could transform computer security

The key to computer security: not relying on the computer

How hardware wallets could transform computer security

66 Group Results

Research Group

Advanced Network Architecture Group

The challenge that motivates the ANA group is to foster a healthy future for the Internet. The interplay of private sector investment, public sector regulation and public interest advocacy, as well as the global diversity in drivers and aspirations, makes for an uncertain future.

David Clark

Karen Sollins

Leads

David Clark

Karen Sollins

Research Areas

Impact Areas

Lead

David Clark

Karen Sollins

David Clark

Karen Sollins

Research Group

Anyscale Learning for All ALFA

Our vision is data-driven machine learning systems that advance the quality of healthcare, the understanding of cyber arms races and the delivery of online education.

Una-May O'Reilly

Leads

Una-May O'Reilly

Research Areas

Impact Areas

Lead

Una-May O'Reilly

Research Group

Applied Computing Group

We design software for high performance computing, develop algorithms for numerical linear algebra, and research random matrix theory and its applications.

Alan Edelman

Leads

Alan Edelman

Research Areas

Impact Areas

Lead

Alan Edelman

Research Group

Broderick Lab

We work in the areas of statistics and machine learning.

Tamara Broderick

Leads

Tamara Broderick

Research Areas

Impact Areas

Lead

Tamara Broderick

Research Group

Center for Brains, Minds and Machines

Our main goal is developing a computationally based understanding of human intelligence and establishing an engineering practice based on that understanding.

Tomaso Poggio

Leads

Tomaso Poggio

Research Areas

Impact Areas

Lead

Tomaso Poggio

Research Group

Clinical Decision-Making Group

We focus on furthering the application of technology and artificial intelligence in medicine and health-care.

+11

Peter Szolovits

Leads

Peter Szolovits

Research Areas

Impact Areas

Lead

Peter Szolovits

+11

Peter Szolovits

Research Group

Clinical Machine Learning Group

Our group is interested in using machine learning and artificial intelligence to transform health care.

David Sontag

Leads

David Sontag

Research Areas

Impact Areas

Lead

David Sontag

Research Group

Commit Group

We focus on finding novel approaches to improve the performance of modern computer systems without unduly increasing the complexity faced by application developers, compiler writers, or computer architects.

Saman Amarasinghe

Leads

Saman Amarasinghe

Research Areas

Computer Architecture

Impact Areas

Lead

Saman Amarasinghe

Research Group

Complexity Theory Group

Our interests span quantum complexity theory, barriers to solving P versus NP, theoretical computer science with a focus on probabilistically checkable proofs (PCP), pseudo-randomness, coding theory, and algorithms.

Leads

Shafi Goldwasser

Ronitt Rubinfeld

Michael Sipser

Ryan Williams

Virginia Vassilevska Williams

Research Areas

Impact Areas

Lead

Shafi Goldwasser

Ronitt Rubinfeld

Michael Sipser

Ryan Williams

Virginia Vassilevska Williams

Research Group

Computation and Biology

Our lab focuses on designing algorithms to gain biological insights from advances in automated data collection and the subsequent large data sets drawn from them.

Bonnie Berger

Leads

Bonnie Berger

Research Areas

Impact Areas

Lead

Bonnie Berger

Research Group

Computation Structures Group

Our mission is fostering the creation and development of high-performance, reliable and secure computing systems that are easy to interact with.

+29

Leads

Srini Devadas

Daniel Sanchez

Armando Solar-Lezama

Arvind

Research Areas

Computer Architecture

Impact Areas

Lead

Srini Devadas

Daniel Sanchez

Armando Solar-Lezama

Arvind

+29

Research Group

Computational Biology Group

We seek to understand the mechanistic basis of human disease, using a combination of computational and experimental techniques.

Manolis Kellis

Leads

Manolis Kellis

Research Areas

Impact Areas

Lead

Manolis Kellis

Research Group

Computational Cognitive Science Group

We study the computational basis of human learning and inference.

Joshua Tenenbaum

Leads

Joshua Tenenbaum

Research Areas

Impact Areas

Lead

Joshua Tenenbaum

Research Group

Computational Connectomics Group

Our group’s goal is to create, based on such microscopic connectivity and functional data, new mathematical models explaining how neural tissue computes.

Nir Shavit

Leads

Nir Shavit

Research Areas

Impact Areas

Lead

Nir Shavit

Research Group

Computational Fabrication Group

Our research centers on digital manufacturing, 3D printing and computer graphics, as well as computational photography and displays, and virtual humans and robotics.

Wojciech Matusik

Leads

Wojciech Matusik

Research Areas

Impact Areas

Lead

Wojciech Matusik

Research Group

Computational Genomics Group

We develop new machine learning techniques and algorithms to model the transcriptional regulatory networks that control gene expression programs in living cells.

Dave Gifford

Leads

Dave Gifford

Research Areas

Impact Areas

Lead

Dave Gifford

Research Group

Computational Perception & Cognition

We combine methods from computer science, neuroscience and cognitive science to explain and model how perception and cognition are realized in human and machine.

Aude Oliva

Leads

Aude Oliva

Research Areas

Impact Areas

Lead

Aude Oliva

Research Group

Computer Graphics Group

Our group focuses on synthetic image generation and computational photography.

+20

Leads

Fredo Durand

William Freeman

Wojciech Matusik

Justin Solomon

Research Areas

Impact Areas

Lead

Fredo Durand

William Freeman

Wojciech Matusik

Justin Solomon

+20

Research Group

Computer-Aided Programming

We develop techniques and tools that exploit automated reasoning and large amounts of computing power to tackle challenging programming problems

Armando Solar-Lezama

Leads

Armando Solar-Lezama

Research Areas

Impact Areas

Lead

Armando Solar-Lezama

Research Group

Cryptography and Information Security Group

We seek to develop techniques for securing tomorrow's global information infrastructure by exploring theoretical foundations, near-term practical applications, and long-range speculative research.

Leads

Shafi Goldwasser

Silvio Micali

Ronald Rivest

Vinod Vaikuntanathan

Butler Lampson

Research Areas

Impact Areas

Lead

Shafi Goldwasser

Silvio Micali

Ronald Rivest

Vinod Vaikuntanathan

Butler Lampson

Research Group

Data Systems Group

We conduct research on all areas of database systems and information management.

+19

Leads

Sam Madden

Michael Stonebraker

Tim Kraska

Research Areas

Impact Areas

Lead

Sam Madden

Michael Stonebraker

Tim Kraska

+19

Research Group

Data-Driven Inference Group

We use machine learning and computer vision to improve outcomes in medicine, finance, and sports

John Guttag

Leads

John Guttag

Research Areas

Impact Areas

Lead

John Guttag

Research Group

Decentralized Information Group

We are investigating decentralized technologies that affect social change.

Lalana Kagal

Tim Berners-Lee

Leads

Lalana Kagal

Tim Berners-Lee

Research Areas

Impact Areas

Lead

Lalana Kagal

Tim Berners-Lee

Lalana Kagal

Tim Berners-Lee

Research Group

Distributed Robotics Laboratory

We aim to develop the science of autonomy toward a future with robots and AI systems integrated into everyday life, supporting people with cognitive and physical tasks.

+19

Daniela Rus

Leads

Daniela Rus

Research Areas

Natural Language Processing Group

Impact Areas

Lead

Daniela Rus

+19

Daniela Rus

289 Project Results

Project

Aspect-Augmented Adversarial Networks for Domain Adaptation

We propose a novel aspect-augmented adversarial network for cross-aspect and cross-domain adaptation tasks. The effectiveness of our approach suggests the potential application of adversarial networks to a broader range of NLP tasks for improved representation learning, such as machine translation and language generation.

Regina Barzilay

Tommi Jaakkola

Leads

Regina Barzilay

Tommi Jaakkola

Research Areas

Regina Barzilay

Tommi Jaakkola

Project

Aurum: Large Scale Data Discovery

Aurum is a data discovery system that works at large scale, helping people find relevant data.

Sam Madden

Michael Stonebraker

Leads

Sam Madden

Michael Stonebraker

Research Areas

Impact Areas

Model-Based Embedded and Robotics Systems Group

Sam Madden

Michael Stonebraker

Project

Automated Attack Tree Generation for Critical Infrastructure

Using AI methods, we are developing an attack tree generator that automatically enumerates cyberattack vectors for industrial control systems in critical infrastructure (electric grids, water networks and transportation systems). The generator can quickly assess cyber risk for a system at scale.

Howard Shrobe

Leads

Howard Shrobe

Research Areas

Impact Areas

Spoken Language Systems Group

Howard Shrobe

Project

Automatic Speech Recognition

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

Wei-Ning Hsu

David Harwath

Sameer Khurana

Di-Chia Chueh

Jim Glass

Research Areas

Impact Areas

Project

Autonomous Vehicle Databases

The impending success of AV technology will create vehicles that collect sensor data at a high rate.

Michael Stonebraker

Sam Madden

Leads

Michael Stonebraker

Sam Madden

Research Areas

Impact Areas

Clinical Decision-Making Group

Michael Stonebraker

Sam Madden

Project

AWE-CM Vectors: Augmenting Word Embeddings with a Clinical Metathesaurus

Adding domain knowledge to word embeddings.

Peter Szolovits

Leads

Peter Szolovits

Research Areas

Impact Areas

Cryptography and Information Security Group

Peter Szolovits

Project

Basing Cryptography on Structured Hardness

We aim to base a variety of cryptographic primitives on complexity theoretic assumptions. We focus on the assumption that there exist highly structured problems --- admitting so called "zero-knowledge" protocols --- that are nevertheless hard to compute

Akshay Degwekar

Prashant Vasudevan

Leads

Akshay Degwekar

Prashant Vasudevan

Research Areas

Learning and Intelligent Systems

Akshay Degwekar

Prashant Vasudevan

Project

Bayesian Optimization for Global Optimization of Expensive Black-box Functions

Machine Learning

We study the fundamentals of Bayesian optimization and develop efficient Bayesian optimization methods for global optimization of expensive black-box functions originated from a range of different applications.

Zi Wang

Leads

Zi Wang

Research Areas

Impact Areas

Computational Cognitive Science Group

Zi Wang

Project

Beating the World's Best at Super Smash Bros. with Deep Reinforcement Learning

We use deep reinforcement learning and self-play to train human-level agents for a multiplayer fighting game.

Leads

Project

Bellmania

Supertech Research Group

Computer-Aided Programming

Deductive synthesis for large-scale implementations of dynamic programming algorithms

Leads

Research Areas

Distributed Robotics Laboratory

Project

Better Models for Ride-Sharing

Traffic is not just a nuisance for drivers: It’s also a public health hazard and bad news for the economy.

Leads

Research Areas

Impact Areas

Energy

Project

Blood Pressure Imager

Development of affordable wearable continuous blood pressure monitor based on radial arterial pulse imaged from the skin surface of human wrist

Mumin Jin

Aya G. Halawi

Jianhua Li

Leads

Abhijit Biswas

Ted Adelson

Mandayam A. Srinivasan

Mohan Thanikachalam

Research Areas

Computation Structures Group

Mumin Jin

Aya G. Halawi

Jianhua Li

Project

BlueDBM: Distributed Flash Storage for Big Data Analytics

BlueDBM is an architecture of computer clusters consisting of fast distributed flash storage and in-storage accelerators, which often outperforms larger and more expensive clusters in applications such as graph analytics.

SangWoo Jun

Leads

SangWoo Jun

Research Areas

Computer Architecture

Impact Areas

Geometric Data Processing Group

SangWoo Jun

Project

Boundary Element Method for Shape Analysis and Geometry Processing

We are working on methods to analyze and process 3D shapes from representations of their boundaries; we focus on extrinsic geometry, that is, how the surface curves and bends through surrounding space.

Mirela Ben-Chen

Iosif Polterovich

Yu Wang

Justin Solomon

Leads

Yu Wang

Justin Solomon

Research Areas

Distributed Robotics Laboratory

Mirela Ben-Chen

Iosif Polterovich

Yu Wang

Justin Solomon

Project

Brain-Controlled Robots

This project aims to let people correct robot mistakes with nothing more than their brain signals - to allow robots to adapt to humans rather than the other way around

Frank H. Guenther

Daniela Rus

Joseph DelPreto

Leads

Daniela Rus

Joseph DelPreto

Research Areas

Frank H. Guenther

Daniela Rus

Joseph DelPreto

Project

Bridging Theory and Practice in Shared-Memory Parallel Algorithm Design

This project aims to design parallel algorithms for shared-memory machines that are efficient both in theory and also in practice.

Julian Shun

Leads

Julian Shun

Research Areas

Impact Areas

Julian Shun

Project

Building a Scalable Database for Autonomous Vehicles

We are building a database for autonomous vehicle sensor data that addresses the challenges presented by the potential scale of autonomous vehicle data and the unique characteristics of the data.

Leads

Aaron Zalewski

Michael Stonebraker

Sam Madden

Oscar Ricardo Moll Thomae

Research Areas

Decentralized Information Group

Project

The Car Can Explain!

Developing techniques to allow self-driving cars and other AI-driven systems to explain behaviors and failures.

Leads

Gerald Sussman

Lalana Kagal

Daniel Weitzner

Research Areas

Impact Areas

Project

Cardiac MRI analysis

We develop image analysis algorithms for whole-heart cardiac MRI in patients with severe congenital heart disease.

Polina Golland

Leads

Polina Golland

Research Areas

Impact Areas

Polina Golland

Project

Chameleon: Using Machine Learning to Make Databases Faster!

Our goal is to build a database framework in which the database predicts user queries and builds indexes in advance to allow future queries to run faster.

Leads

Albert Kim

Sam Madden

Aditya Parameswaran

Research Areas

Imagination, Computation, and Expression Laboratory (ICE Lab)

Project

Changing Minds via Roleplay in Interactive Digital Media

We aim to study the impact of computer-supported roleplaying in changing social perspectives of digital media users. Such media could take the form of videogames, VR systems, training software, and other types of interactive narrative technology.

Pablo Ortiz

D. Fox Harrell

Leads

Pablo Ortiz

D. Fox Harrell

Research Areas

Impact Areas

Pablo Ortiz

D. Fox Harrell

Project

Characterizing the Sensitivity of Vision-in-the-Loop Driving Controllers Using CG

We work on understanding and improving vision algorithms used for self driving cars, by introducing synthetic data-sets to the loop.

Leads

Research Areas

Impact Areas

Project

Chest X-Ray Analysis

We develop machine learning algorithms to automatically quantify the severity of pulmonary edema from chest x-rays.

Polina Golland

Leads

Polina Golland

Research Areas

Impact Areas

Polina Golland

Project

CilkPride

Usable Programming Group

CilkPride is a programming environment that aims to make performance and safety information always available and appropriately visible to the programmer.

Charles E. Leiserson

Rob Miller

Leads

Charles E. Leiserson

Rob Miller

Research Areas

Internet Policy Research Initiative

Charles E. Leiserson

Rob Miller

1530 People Results

Scott Aaronson

Visiting Professor

E aaronson@csail.mit.edu

T 324-8356

Nezar Abdennur

Graduate Student

E nezar@MIT.EDU

Zachary Abel

Temporary Lecturer

E zabel@mit.edu

PI
Core/Dual

Hal Abelson

Professor

Programming, privacy, App Inventor

E hal@mit.edu

T 253-5856

Lead

MIT App Inventor

Member

Keys Under Doormats

Keeping America Safe: Toward More Secure Networks for Critical Sectors

Programming, privacy, App Inventor

Maleen Abeydeera

Graduate Student

E maleen@csail.mit.edu

Member

Pervasive Parallelism with the Swarm Architecture

Madeline Abrahams

Super UROP

Murad Abu-Khalaf

Program Manager, Toyota-CSAIL Joint Research Center

E murad@mit.edu

T 452-2859

Grace Abuhamad

Graduate Student

E abuhamad@mit.edu

Mazdak Abulnaga

Graduate Student

medical vision

E abulnaga@mit.edu

Member

Monitoring Fetal Health

medical vision

RM 32-G528B

PI
Core/Dual

Ted Adelson

Professor

Vision, touch sensing, robotics

E adelson@csail.mit.edu

T 253-0645

Lead

Blood Pressure Imager

Member