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.

+10

Peter Szolovits

Leads

Peter Szolovits

Research Areas

Impact Areas

Lead

Peter Szolovits

+10

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 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, computational photography, digital manufacturing, and geometry.

Leads

Fredo Durand

William Freeman

Wojciech Matusik

Justin Solomon

Research Areas

Impact Areas

Lead

Fredo Durand

William Freeman

Wojciech Matusik

Justin Solomon

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.

+13

Daniela Rus

Leads

Daniela Rus

Research Areas

Impact Areas

Lead

Daniela Rus

+13

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.

Polina Golland

Leads

Polina Golland

Research Areas

Impact Areas

Lead

Polina Golland

Research Group

Model-Based Embedded and Robotics Systems Group

We are working to elevate robots from mechanical creations controlled by low-level scripts with a considerable amount of human guidance to truly cognitive robots.

Brian Williams

Leads

Brian Williams

Research Areas

Impact Areas

Lead

Brian Williams

305 Project Results matching all criteria

Project

Driver-Friendly Bilateral Control for Suppressing Traffic Instabilities

We are studying how best to implement bilateral control and make it acceptable to drivers

Berthold Horn

Leads

Berthold Horn

Research Areas

Impact Areas

Berthold Horn

Project

Computational Bounce Flash for Indoor Portraits

Computer Graphics Group

To achieve high-quality photo lighting in challenging environments, our prototype camera dynamically reconstructs a 3D scene model and directs a motor-controlled flash head at nearby walls and ceilings for soft indirect illumination.

Lukas Murmann

Leads

Lukas Murmann

Research Areas

Impact Areas

Lukas Murmann

Project

Predictive Vision

We've developed an algorithm to anticipate visual events that may happen in the future

Leads

Research Areas

Computational Cognitive Science Group

Project

Neural Physics Engine

Spoken Language Systems Group

We've developed an object-based neural network architecture for learning predictive models of intuitive physics that extrapolates to variable object count and variable scene configurations with only spatially and temporally local computation.

Leads

Project

Using Computers to Eat Healthier

Our goal is to build an AI-powered personal digital nutritionist that enables users to track the food they eat simply by speaking or typing natural English phrases.

Leads

Research Areas

Impact Areas

Model-Based Embedded and Robotics Systems Group

Project

RADMAX

This project focuses on holistic decision making for network optimization.

Brian Williams

Howard Shrobe

Leads

Brian Williams

Howard Shrobe

Research Areas

Computational Cognitive Science Group

Brian Williams

Howard Shrobe

Project

A Counterfactual Simulation Model of Causal Judgment

We develop a computational model that explains how people make causal judgments in physical scenes by mentally simulating counterfactual outcomes and comparing those to what actually happened.

Leads

Research Areas

Impact Areas

Project

Artificial Co-driver

Computer Graphics Group

By observing driver in real road situations, we learn a computer assistant that can make driving easier, safer and more enjoyable.

Leads

Research Areas

Impact Areas

Natural Language Processing Group

Project

Aspect-Augmented Adversarial Networks for Domain Adaptation

Vertical AI Community of Research

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

SoundNet

This project focuses on learning sound representations from unlabeled video

Leads

Research Areas

Project

Where Are They Looking?

Our goal is to build a system that predicts where people are looking in images. Given an image and the location of a head, our approach follows the gaze of the person and identifies the object being looked at.

Leads

Research Areas

Impact Areas

Project

Predictive Modeling for Database Elasticity

This project shows that we can successfully use predictive modeling to enable a database cluster to elastically expand or contract in anticipation of changes in the workload.

Michael Stonebraker

Leads

Michael Stonebraker

Research Areas

Michael Stonebraker

Project

Covering All K-mers Using Joker Characters

Computation and Biology

We developed a new algorithm to generate compact sequence sets covering all k-mers using joker characters.

Bonnie Berger

Leads

Bonnie Berger

Research Areas

Model-Based Embedded and Robotics Systems Group

Bonnie Berger

Project

Finite Approximations of Infinite Models

Machine Learning

Many modern Bayesian models involve infinitely many latent parameters. We seek to develop finite approximations which are more tractable for use in practice, and characterize their incurred error.

Leads

Project

Tractable Models of Sparse Networks

Machine Learning

Most popular, tractable statistical models for network data inherently assume the network is dense, although this is rarely true in practice; we propose a new modeling framework that correctly captures sparse networks.

Leads

Project

Geordi: A Driver's Assistant for Risk-bounded Maneuvering

Our goal is to create an online risk-aware planner for vehicle maneuvers that can make driving safer and less stressful through a “parallel” autonomous system that assists the driver by watching for risky situations, and by helping the driver take proactive, compensating actions before they become crises.

Brian Williams

Leads

Brian Williams

Research Areas

Impact Areas

Parallel and Distributed Operating Systems

Brian Williams

Project

Noria: a new data-flow system for web applications

We're developing a flexible, high-performance storage architecture for database-backed applications, based on a dynamic set of queries specified by the developer which Soup automatically optimizes.

Jon Gjengset

Malte Schwarzkopf

Leads

Jon Gjengset

Malte Schwarzkopf

Research Areas

Impact Areas

Jon Gjengset

Malte Schwarzkopf

Project

Single-Image 3D Interpreter Network

We aim to understand 3D object structure from a single image. We propose an end-to-end framework which sequentially estimates 2D keypoint heatmaps and 3D object structure, by training it on both real 2D-annotated images and synthetic 3D data and by integrating a 3D-to-2D projection layer.

Leads

Research Areas

Impact Areas

Distributed Robotics Laboratory

Project

Printable Hydraulics

Printable Hydraulics allows fluid-actuated robots to be automatically fabricated using 3D printers.

Youbin Kim

Leads

Research Areas

Impact Areas

Energy

Youbin Kim

Project

Matrix Permanents and Linear Optics

Complexity Theory Group

We use tools from quantum physics to prove new results in classical complexity.

Leads

Research Areas

Project

Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks

In our work we developed a model that is able to synthesize many probable future frames with just a single image as input.

Leads

Research Areas

Decentralized Information Group

Project

Solid: Social Linked Data

Computing & Society Community of Research

Solid aims to radically change the way Web applications work today, resulting in true data ownership as well as improved privacy.

Tim Berners-Lee

Lalana Kagal

Leads

Tim Berners-Lee

Lalana Kagal

Research Areas

Impact Areas

Internet of Things

Tim Berners-Lee

Lalana Kagal

Project

AdaptDB: Adaptive Partitioning for Distributed Joins

Our goal is to develop an adaptive storage manager for analytical database workloads in a distributed setting. It works by partitioning datasets across a cluster and incrementally refining data partitioning as queries are run.

Leads

Research Areas

Impact Areas

Project

Wikum: Bridging Discussion Systems and Wikis with Collective Summarization

Haystack Group

We build tools to allow a community of people to collectively summarize large discussions online and manage knowledge embedded within these discussions.

David Karger

Leads

David Karger

Research Areas

Impact Areas

Internet Policy Research Initiative

David Karger

1128 People Results matching all criteria

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

Computing & Society Community of Research

Programming, privacy, App Inventor

Maleen Abeydeera

Graduate Student

E maleen@csail.mit.edu

Member

Pervasive Parallelism with the Swarm Architecture

Madeline Abrahams

Super UROP

E maddyabr@MIT.EDU

Murad Abu-Khalaf

Program Manager, Toyota-CSAIL Joint Research Center

E murad@mit.edu

T 452-2859

Mazdak Abulnaga

Graduate Student

medical vision

E abulnaga@mit.edu

Member

Monitoring Fetal Health

Medical Vision Group

Geometric Data Processing Group

Geometry and topology for scientific computing and shape analysis

medical vision

Sara Achour

Graduate Student

E sachour@mit.edu

Kenneth Acquah

Super UROP

E kkacquah@mit.edu

Samuel Acquaviva

UROP

E samacqua@mit.edu

Ariana Adames

UROP

E aiadames@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

Embodied Intelligence Community of Research

Blood Pressure Imager

Member

Visual Computing Community of Research

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

E PULKITAG@MIT.EDU

RM 32-386D

Leandro Agudelo

Research Scientist

Systems Genomics, CompBio, Topological Integrative Biology, Biology

E lagudelo@csail.mit.edu

Systems Genomics, CompBio, Topological Integrative Biology, Biology

Giovanni Ahern

UROP

E gahern@mit.edu

Peter Ahrens

Graduate Student

E pahrens@mit.edu

Marc Aidinoff

Temporary Graduate Student

E Aidinoff@mit.edu

RM 32-G528A

Anurag Ajay

Graduate Student

E aajay@mit.edu

Member

Learning and Intelligent Systems

1625 News Results matching all criteria

January 13 '21

To the brain, reading computer code is not the same as reading language

Neuroscientists find that interpreting code activates a general-purpose brain network, but not language-processing centers.

To the brain, reading computer code is not the same as reading language

AI & ML Graphics & Vision

January 13 '21

Professor Antonio Torralba elected 2021 AAAI Fellow

EECS faculty head of artificial intelligence and decision making honored for significant and extended contributions to the field of AI.

Professor Antonio Torralba elected 2021 AAAI Fellow

AI & ML Transportation

December 10 '20

Explained: Levels of autonomy in self-driving cars

A six-level system classifies the varying degrees of vehicle autonomy

Explained: Levels of autonomy in self-driving cars

This is not a photograph - every object in this image was auto-created and textured using the team's MATch software

December 09 '20

Automating material-matching for movies

Animators spend hours adding textures to objects in films and video games. A new machine learning system makes the process simpler and easier.

Automating material-matching for movies

Enzyme allows you to import arbitrary foreign code into systems like TensorFlow without having to rewrite it.

December 07 '20

More compatible coding for machine learning

CSAIL's compiler plug-in allows you to import arbitrary foreign code into systems like TensorFlow without having to rewrite it.

More compatible coding for machine learning

Algorithms & Theory AI & ML

December 07 '20

Building machines that better understand human goals

A new algorithm capable of inferring goals and plans could help machines better adapt to the imperfect nature of human planning

Building machines that better understand human goals

December 07 '20

Better learning with shape-shifting objects

MIT study shows the power of adaptive training tools, like a basketball hoop that shrinks and raises as you make shots

Better learning with shape-shifting objects

Systems & Networking

December 03 '20

Hari Balakrishnan awarded Infosys Prize for 2020

The prestigious 2020 Infosys Prize in Engineering and Computer Science was awarded to Hari Balakrishnan, the Fujitsu professor of Electrical Engineering and Computer Science, co-leader of the Networks and Mobile Systems Group within CSAIL, and co-director of MIT’s Center for Wireless Networks and Mobile Computing, for his outstanding contributions to science and research.

Hari Balakrishnan awarded Infosys Prize for 2020

Algorithms & Theory AI & ML

December 02 '20

Shrinking massive neural networks used to model language

A new approach could lower computing costs and increase accessibility to state-of-the-art natural language processing.

Shrinking massive neural networks used to model language

December 02 '20

This 3D printer doesn’t gloss over the details

A new system enables realistic variations in glossiness across a 3D-printed surface. The advance could aid fine art reproduction and the design of prosthetics.

This 3D printer doesn’t gloss over the details

December 02 '20

Hot Topics in Computing: Creating, Weaponizing, and Detecting Deep Fakes

On December 2, 2020 Prof Hany Farid presented a talk for Hot Topics in Computing series entitled Creating, Weaponizing, and Detecting Deep Fakes

Hot Topics in Computing: Creating, Weaponizing, and Detecting Deep Fakes

December 02 '20

Study: adding peptides to COVID-19 vaccines improves effectiveness for under-represented populations

MIT CSAIL researchers showed that the vaccines’ effectiveness may vary depending on a person’s race, and said that the vaccines should be tested robustly across populations with diverse genetic backgrounds.

Study: adding peptides to COVID-19 vaccines improves effectiveness for under-represented populations

Algorithms & Theory Robotics

November 30 '20

Computer-aided creativity in robot design

MIT researchers’ new system optimizes the shape of robots for traversing various terrain types.

Computer-aided creativity in robot design

A neural network learns when it should not be trusted

AI & ML Robotics Transportation

November 24 '20

A neural network learns when it should not be trusted

A faster way to estimate uncertainty in AI-assisted decision-making could lead to safer outcomes.

A neural network learns when it should not be trusted

Algorithm contributions by birth country

November 18 '20

Study: computing is made in America (but not just by Americans)

It’s no secret that algorithms run the world, powering everything from Google’s search results to Uber’s car-pool capabilities. But farther under the hood are a more fundamental set of algorithms that underpin computing: if Google PageRank is the engine, these algorithms are the parts it’s built from.

Study: computing is made in America (but not just by Americans)

November 17 '20

Hot Topics in Computing: Fireside Talk with Eric Schmidt

On November 17, 2020 the Schwarzman College of Computing and Computer Science & Artificial Intelligence Lab hosted a special Hot Topics in Computing event featuring a fireside talk with former Google CEO & Chairman, and Co-Founder, Schmidt Futures, Eric Schmidt.

Hot Topics in Computing: Fireside Talk with Eric Schmidt

November 16 '20

MIT experts: no, don’t use blockchain to vote

Cybersecurity researchers say it would increase the risk of country-wide failures that could de-legitimize entire elections

MIT experts: no, don’t use blockchain to vote

November 10 '20

Neural networks that imagine others’ states of mind

A CSAIL-led team has trained a neural network to learn NASCAR-style driving maneuvers purely from looking at a sequence of images taken from a two-person racing game.

Neural networks that imagine others’ states of mind

Algorithms & Theory AI & ML Computational Biology Health Care

November 04 '20

Algorithm reduces unnecessary use of antibiotics for UTIs

Machine learning model predicts probability that a patient’s UTI can be treated by various antibiotics

Algorithm reduces unnecessary use of antibiotics for UTIs

Algorithms & Theory Robotics Transportation

October 26 '20

Autonomous boats could be your next ride

Five years in the making, MIT’s autonomous floating vessels get a size upgrade and learn a new way to communicate aboard the waters.

Autonomous boats could be your next ride

Robotics Health Care

October 22 '20

What to Expect When You’re Expecting Robots

Book co-authored by Associate Professor Julie Shah and Laura Major SM ’05 explores a future populated with robot helpers.

What to Expect When You’re Expecting Robots

October 21 '20

Robot stably swings objects into specific poses

We humans can pick up an object we’ve never seen and move it gracefully. An MIT team is working to train robots to do the same.

Robot stably swings objects into specific poses

Human-Computer Interaction

October 21 '20

Electronic design tool morphs interactive objects

A new system lets users digitally model an object’s form and electronic function in one integrated space

Electronic design tool morphs interactive objects

The team has been able to decipher lost languages like Ugaritic

October 21 '20

Translating lost languages using machine learning

System developed at MIT CSAIL aims to help linguists decipher languages that have been lost to history.

Translating lost languages using machine learning

78 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

Algorithms Group

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

Leads

Costis Daskalakis

Erik Demaine

Michael Goemans

Piotr Indyk

David Karger

Jonathan Kelner

Tom Leighton

Charles E. Leiserson

Aleksander Madry

Ankur Moitra

Ronitt Rubinfeld

Nir Shavit

Ryan Williams

Virginia Vassilevska Williams

Research Areas

Impact Areas

Lead

Costis Daskalakis

Erik Demaine

Michael Goemans

Piotr Indyk

David Karger

Jonathan Kelner

Tom Leighton

Charles E. Leiserson

Aleksander Madry

Ankur Moitra

Ronitt Rubinfeld

Nir Shavit

Ryan Williams

Virginia Vassilevska Williams

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.

Leads

Research Areas

Impact Areas

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.

Una-May O'Reilly

Leads

Una-May O'Reilly

Research Areas

Impact Areas

Lead

Una-May O'Reilly

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 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.

Aleksander Madry

Leads

Aleksander Madry

Research Areas

Impact Areas

Lead

Aleksander Madry

Research Group

Clinical Decision-Making Group

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

+10

Peter Szolovits

Leads

Peter Szolovits

Research Areas

Impact Areas

Lead

Peter Szolovits

+10

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

Community of Research

Cognitive AI Community of Research

This CoR aims to develop AI technology that synthesizes symbolic reasoning, probabilistic reasoning for dealing with uncertainty in the world, and statistical methods for extracting and exploiting regularities in the world, into an integrated picture of intelligence that is informed by computational insights and by cognitive science.

Howard Shrobe

Leads

Howard Shrobe

Research Areas

Impact Areas

Lead

Howard Shrobe

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.

+21

Leads

Srini Devadas

Daniel Sanchez

Armando Solar-Lezama

Arvind

Research Areas

Computer Architecture

Impact Areas

Lead

Srini Devadas

Daniel Sanchez

Armando Solar-Lezama

Arvind

+21

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 Design and 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, computational photography, digital manufacturing, and geometry.

Leads

Fredo Durand

William Freeman

Wojciech Matusik

Justin Solomon

Research Areas

Impact Areas

Lead

Fredo Durand

William Freeman

Wojciech Matusik

Justin Solomon

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

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.

Daniel Weitzner

Leads

Daniel Weitzner

Research Areas

Impact Areas

Lead

Daniel Weitzner

305 Project Results

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.

Leads

Research Areas

Impact Areas

Computational Design and Fabrication Group

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

Computation Structures Group

James Minor

Project

[Inactive] T-1000: A Thousand-Core Coherent Shared Memory System

(This project is no longer active.) The T-1000, a prototype system of a thousand realistic processors embedded throughout an ensemble of interconnected FPGAs, seeks to demonstrate the scalability of timestamp-based cache coherence protocols on distributed shared memory systems.

Quan Nguyen

Leads

Quan Nguyen

Research Areas

Computer Architecture

Computational Cognitive Science Group

Quan Nguyen

Project

A Counterfactual Simulation Model of Causal Judgment

We develop a computational model that explains how people make causal judgments in physical scenes by mentally simulating counterfactual outcomes and comparing those to what actually happened.

Leads

Research Areas

Impact Areas

Computation Structures Group

Project

A new way of handling all-to-all broadcast

We design a new all-to-all broadcasts scheme with significantly less communication cost using aggregate signatures.

Alin Tomescu

Jun Wan

Leads

Jun Wan

Research Areas

Alin Tomescu

Jun Wan

Project

A Simplified and Extensible Cilk Runtime for Research

CilkS is a new runtime system for the Cilk multithreaded programming environment which makes it easy to experiment with new algorithms, data structures, and programming linguistics.

Charles E. Leiserson

Tao Schardl

Leads

Charles E. Leiserson

Tao Schardl

Research Areas

Learning and Intelligent Systems

Charles E. Leiserson

Tao Schardl

Project

Active Learning of Models for Planning

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.

Leslie Kaelbling

Tomas Lozano-Perez

Leads

Leslie Kaelbling

Tomas Lozano-Perez

Research Areas

Impact Areas

Leslie Kaelbling

Tomas Lozano-Perez

Project

AdaptDB: Adaptive Partitioning for Distributed Joins

Leads

Research Areas

Impact Areas

Anyscale Learning for All ALFA

Project

Adversarial Cyber Security

Applied Machine Learning Community of Research

Our goal is to understand the nature of cyber security arms races between malicious and bonafide parties. Our vision is autonomous cyber defenses that anticipate and take measures against counter attacks.

Una-May O'Reilly

Leads

Una-May O'Reilly

Research Areas

Impact Areas

Networks and Mobile Systems

Una-May O'Reilly

Project

Aggregate Congestion Control

Develop a method for sending persistently backlogged traffic on the Internet while adapting to link conditions dynamically.

Akshay Narayan

Francis Cangialosi

Leads

Akshay Narayan

Francis Cangialosi

Research Areas

Impact Areas

Imagination, Computation, and Expression Laboratory (ICE Lab)

Akshay Narayan

Francis Cangialosi

Project

AIRvatar System: A Framework for Analyzing Virtual Identities

AIRvatar is a system that telemetrically collects and analyzes fine-grained data on users’ virtual identities and the process used to create them.

D. Fox Harrell

Leads

D. Fox Harrell

Research Areas

Impact Areas

D. Fox Harrell

Project

Algebraic Techniques for Algorithm Design

We work on improving the algorithms for algebraic problems like matrix multiplication, and using these to design algorithms for fundamental non-algebraic problems.

Virginia Vassilevska Williams

Leads

Virginia Vassilevska Williams

Research Areas

Virginia Vassilevska Williams

Project

Algorithmic Aspects of Performance Engineering

Supertech Research Group

The project concerns algorithmic solutions for writing fast codes.

Leads

Research Areas

Impact Areas

Project

Alloy

Software Design Group

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.

Daniel Jackson

Leads

Daniel Jackson

Research Areas

Impact Areas

Daniel Jackson

Project

Amoeba: A shape changing storage system for big data

Amoeba is a distributed storage system that efficiently supports ad-hoc and exploratory analytics using adaptive data partitioning

Alekh Jindal

Leads

Research Areas

Theory of Distributed Systems Group

Alekh Jindal

Project

An Algorithmic Theory of Brain Networks

We are developing an algorithmic theory for brain networks, based on simple synchronized stochastic graph-based neural network models.

Nancy Lynch

Leads

Nancy Lynch

Research Areas

Computer-Aided Programming

Nancy Lynch

Project

An Interlock for Self Driving Cars

Software Design Group

Vertical AI Community of Research

Self-driving cars are likely to be safer, on average, than human-driven cars. But they may fail in new and catastrophic ways that a human driver could prevent. This project is designing a new architecture for a highly dependable self-driving car.

Daniel Jackson

Armando Solar-Lezama

Leads

Daniel Jackson

Armando Solar-Lezama

Research Areas

Impact Areas

Daniel Jackson

Armando Solar-Lezama

Project

Analyzing Player Profile Data

Developing new methods for analyzing large quantities of player profile data, such as hundreds of thousands of profile images or chat logs.

D. Fox Harrell

Peter Mawhorter

Leads

D. Fox Harrell

Peter Mawhorter

Research Areas

Interactive Robotics Group

D. Fox Harrell

Peter Mawhorter

Project

Apprenticeship Scheduling: Learning to Schedule From Human Experts

Robot scheduling via learning from demonstration for tasks in medicine and more

Leads

Research Areas

Impact Areas

Project

Approximate String Joins with Abbreviations

We propose efficient and effective algorithms to perform approximate string joins with abbreviations in database systems.

Wenbo Tao

Leads

Wenbo Tao

Research Areas

Wenbo Tao

Project

Approximating the diameter of a directed graph

There is a family of approximation algorithms for computing the diameter of an undirected graph that give a time/accuracy trade-off and our goal is to extend these results to directed graphs.

Virginia Vassilevska Williams

Leads

Virginia Vassilevska Williams

Research Areas