Research

Impact Areas

Lead

Alan Edelman

Research Group

Geometric Data Processing Group

Our group studies geometric problems in computer graphics, computer vision, machine learning, optimization, and other disciplines.

Justin Solomon

Leads

Justin Solomon

Research Areas

Impact Areas

Lead

Justin Solomon

Research Group

Supertech Research Group

We investigate the technologies that support scalable high-performance computing, including hardware, software, and theory.

Charles E. Leiserson

Leads

Charles E. Leiserson

Research Areas

Computer Architecture

Impact Areas

Lead

Charles E. Leiserson

Research Group

Quantum Information Science Group

Our research interests center around the capabilities and limits of quantum computers, and computational complexity theory more generally.

Peter Shor

Leads

Peter Shor

Research Areas

Impact Areas

Lead

Peter Shor

Research Group

Theory of Distributed Systems Group

We work on a wide range of problems in distributed computing theory. We study algorithms and lower bounds for typical problems that arise in distributed systems---like resource allocation, implementing shared memory abstractions, and reliable communication.

Nancy Lynch

Leads

Nancy Lynch

Research Areas

Impact Areas

Lead

Nancy Lynch

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.

+10

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

+10

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

Multicore Algorithmics

We develop techniques for designing, implementing, and reasoning about multiprocessor algorithms, in particular concurrent data structures for multicore machines and the mathematical foundations of the computation models that govern their behavior.

Nir Shavit

Leads

Nir Shavit

Research Areas

Impact Areas

Lead

Nir Shavit

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

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

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

Lecturers

Lecturers in CSAIL

Debayan Gupta

Leads

Debayan Gupta

Research Areas

Impact Areas

Lead

Debayan Gupta

Research Group

Theory of Computation Group

Theory research at CSAIL covers a broad spectrum of topics, including algorithms, complexity theory, cryptography, distributed systems, parallel computing and quantum computing.

Leads

Bonnie Berger

Costis Daskalakis

Erik Demaine

Alan Edelman

Michael Goemans

Shafi Goldwasser

Piotr Indyk

David Karger

Jonathan Kelner

Tom Leighton

Charles E. Leiserson

Nancy Lynch

Aleksander Madry

Albert R. Meyer

Silvio Micali

Ankur Moitra

Ronald Rivest

Ronitt Rubinfeld

Nir Shavit

Peter Shor

Vinod Vaikuntanathan

Ryan Williams

Virginia Vassilevska Williams

Research Areas

Impact Areas

Lead

Bonnie Berger

Costis Daskalakis

Erik Demaine

Alan Edelman

Michael Goemans

Shafi Goldwasser

Piotr Indyk

David Karger

Jonathan Kelner

Tom Leighton

Charles E. Leiserson

Nancy Lynch

Aleksander Madry

Albert R. Meyer

Silvio Micali

Ankur Moitra

Ronald Rivest

Ronitt Rubinfeld

Nir Shavit

Peter Shor

Vinod Vaikuntanathan

Ryan Williams

Virginia Vassilevska Williams

47 Project Results matching all criteria

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

Deep Inverse Planning

Deep inverse planning for learning from high-dimensional demonstrations

Leads

Research Areas

Project

Social Network Extraction from GPS Datasets with Coresets

We extract the underlying hidden relations from the given location-based datasets (e.g. GPS data) and we estimate (approximate) the hidden a social network in the data by using a particular data reduction algorithm (i.e., by using coresets).

Daniela Rus

Leads

Daniela Rus

Research Areas

Model-Based Embedded and Robotics Systems Group

Daniela Rus

Project

Uhura: Personal Assistant that Manages Risk

Uhura is an autonomous system that collaborates with humans in planning and executing complex tasks, especially under over-subscribed and risky situations.

Leads

Nikhil Bhargava

Yuening Zhang

Brian Williams

Research Areas

Impact Areas

Entertainment

Manufacturing

Project

Generating Good Adversarial Examples for Neural Networks

Robot Locomotion Group

Our goal is to better understand adversarial examples by 1) bounding the minimum perturbation that needs to be added to a regular input example to cause a given neural network to misclassify it, and 2) generating some adversarial input example with minimum perturbation.

Leads

Research Areas

Learning and Intelligent Systems

Project

Deterministic Algorithms for Robotic Task and Motion Planning

Our goal is to investigate deterministic algorithms for robotic task and motion planning.

Ashwin Deshpande

Leads

Ashwin Deshpande

Research Areas

Data-Driven Inference Group

Impact Areas

Manufacturing

Transportation

Ashwin Deshpande

Project

Hidden Influencers, Risk and Causes of Infection

We aim to study the causes and transmission modes of infectious diseases among members of a community in the presence of hidden, asymptomatic spreaders of the pathogen.

Maggie Makar

John Guttag

Leads

Maggie Makar

John Guttag

Research Areas

Impact Areas

Data-Driven Inference Group

Maggie Makar

John Guttag

Project

Predicting Adverse Events Across Changing Electronic Health Record Systems

Transitioning machine learning models across electronic health record (EHR) versions can be improved by mapping different EHR encodings to a common vocabulary.

Leads

Jen Gong

Tristan Naumann

John Guttag

Peter Szolovits

Research Areas

Impact Areas

Project

Safety Standards for Autonomous Vehicles

In this project, we aim to develop a framework that can ensure and certify the safety of an autonomous vehicle. By leveraging research from the area of formal verification, this framework aims to assess the safety, i.e., free of collisions, of a broad class of autonomous car controllers/planners for a given traffic model.

Leads

Lucas Liebenwein

Cristian-Ioan Vasile

Wilko Schwarting

Daniela Rus

Research Areas

Impact Areas

Transportation

Project

Fast Lightweight Autonomy

The goal of the FLA program is to explore non-traditional perception and autonomy methods that could enable a new class of algorithms for minimalistic high-speed navigation in cluttered environments.

John Carter

Jake Ware

Leads

John Carter

Jake Ware

Research Areas

John Carter

Jake Ware

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

Charles E. Leiserson

Tao Schardl

Project

Programming Abstractions for Dynamic Graph Analytics

We plan to develop a programming abstraction to enable programmers to write efficient parallel programs to process dynamic graphs.

Julian Shun

Leads

Julian Shun

Research Areas

Impact Areas

Julian Shun

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

Planning under uncertainty with complex dynamics

We focus on learning to compute near-optimal plans which leverage environmental contact to mitigate action uncertainty, in hopes of enabling inexpensive robotic manipulators to perform precise assembly tasks.

Charlie Guan

Leads

Charlie Guan

Research Areas

Charlie Guan

Project

Driver-Friendly Bilateral Control for Suppressing Traffic Instabilities

Self-driving cars themselves can solve traffic problems even without global control.

Leads

Research Areas

Learning and Intelligent Systems

Project

Theoretical Analysis of Robotic Planning

We are investigating various theoretical properties of robotic planning frameworks such as decidability and optimality.

Ashwin Deshpande

Leads

Ashwin Deshpande

Research Areas

Ashwin Deshpande

Project

Diversity-inducing Probability Measures

Machine Learning

We aim to understand theory and applications of diversity-inducing probabilities (and, more generally, "negative dependence") in machine learning, and develop fast algorithms based on their mathematical properties.

Leads

Chengtao Li

Stefanie Jegelka

Suvrit Sra

Research Areas

Impact Areas

Project

Practical Secure Computation

Our goal is to bridge theory and practice to create infrastructure that allow computation and multi-party computation without compromising privacy.

Daniela Rus

Danny Feldman

Leads

Daniela Rus

Danny Feldman

Research Areas

Geometric Data Processing Group

Daniela Rus

Danny Feldman

Project

Political Geometry: Establishing Fair Mathematical Standards for Political Redistricting

In collaboration with mathematicians at Tufts University, we are studying how to establish fair, mathematically well-posed, and computationally tractable standards for political redistricting.

Leads

Justin Solomon

Mira Bernstein (Tufts)

Moon Duchin (Tufts)

Ari Nieh (Tufts)

Research Areas

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

Understanding Convergence of Iterative Algorithms

We are trying to develop theoretical tools that can be used to analyze the convergence of iterative algorithms used for non-convex optimization problems.

Costis Daskalakis

Leads

Costis Daskalakis

Research Areas

Costis Daskalakis

Project

Return of the Byzantine Generals

This project studies new solutions to the Byzantine General Problem and its applications in distributed systems and cryptography.

Ling Ren

Srini Devadas

Leads

Ling Ren

Srini Devadas

Research Areas

Ling Ren

Srini Devadas

Project

OpenTuner: An Extensible Framework for Program Autotuning

Commit Group

OpenTuner is a new framework for building domain-specific multi-objective program autotuners.

Leads

Research Areas

Impact Areas

Entertainment

Project

Sublinear Algorithms for Massive Data Problems

This project includes designing efficient algorithms and proving lower bounds for fundamental problems under the models that address big data.

Piotr Indyk

Leads

Piotr Indyk

Research Areas

Piotr Indyk

31 People Results matching all criteria

PI
Core/Dual

Regina Barzilay

Professor

Natural language processing, machine learning

E regina@csail.mit.edu

T 258-5706

Lead

Aspect-Augmented Adversarial Networks for Domain Adaptation

Member

Aspect-Augmented Adversarial Networks for Domain Adaptation

Natural language processing, machine learning

Cenk Baykal

Graduate Student

E baykal@mit.edu

RM 32-376C

Member

Coresets for Machine Learning Algorithms

PI
Core/Dual

Costis Daskalakis

Associate Professor

Theory, algorithms, economics, game theory

E costis@csail.mit.edu

T 253-9643

Lead

Is the Casino using a Riffle Shuffle?

Understanding Convergence of Iterative Algorithms

Theory, algorithms, economics, game theory

PI
Core/Dual

Erik Demaine

Professor

Algorithms, theory, computational geometry, complexity

E edemaine@mit.edu

T 253-6871

Lead

Algorithms, theory, computational geometry, complexity

Martin Demaine

Robotics Engineer

E mdemaine@mit.edu

T 253-7953

PI
Core/Dual

Shafi Goldwasser

Professor

Theory, cryptography, cybersecurity, complexity

E shafi@csail.mit.edu

T 253-5914

Lead

Complexity Theory Group

Splinter: Practical Private Queries on Public Data

Member

Computational Connectomics Group

Theory, cryptography, cybersecurity, complexity

Debayan Gupta

Lecturer

E Debayan@mit.edu

Lead

Lecturers

Joanne Hanley

Administrative Assistant II

Administrative Assistant, Theory of Computation

E joanne@csail.mit.edu

T 253-6054

Member

Computational Connectomics Group

Theory of Distributed Systems Group

Administrative Assistant, Theory of Computation

PI
Core/Dual

Piotr Indyk

Professor

Algorithms, theory, computational geometry

E indyk@csail.mit.edu

T 452-3402

Lead

Sublinear/Streaming Algorithms for Covering Problem

Sublinear Algorithms for Massive Data Problems

Algorithms, theory, computational geometry

PI
Core/Dual

Tommi Jaakkola

Professor

Machine learning, natural language processing, genomics

E tommi@csail.mit.edu

T 253-0440

Lead

Machine Learning

Aspect-Augmented Adversarial Networks for Domain Adaptation

Learning Strategic Games

Structured Prediction Through Randomization

Interpretability in complex machine learning models

Member

Aspect-Augmented Adversarial Networks for Domain Adaptation

Learning Optimal Interventions

Machine learning, natural language processing, genomics

PI
Core/Dual

Lalana Kagal

Principal Research Scientist

Privacy, web decentralization, distributed data

E lkagal@csail.mit.edu

T 253-5845

Lead

Decentralized Information Group

The Car Can Explain!

Internet Policy Research Initiative

Privacy, web decentralization, distributed data

Gautam Kamath

Graduate Student

E kamath@mit.edu

Lead

Efficient Robust Estimation in High Dimensions

PI
Core/Dual

David Karger

Professor

Helping people manage information

E karger@csail.mit.edu

T 258-6167

Lead

Haystack Group

Mavo: Creating Interactive Data-Driven Web Applications by Authoring HTML

Wikum: Bridging Discussion Systems and Wikis with Collective Summarization

Squadbox: Combating Online Harassment using Friendsourced Moderation

Eyebrowse: Social and Public Web Browsing

Helping people manage information

PI
Core/Dual

Dina Katabi

Professor

Wireless, networks, machine learning

E dina@csail.mit.edu

T 324-6027

Lead

Networks at MIT

EQ-Radio: Emotion Recognition using Wireless Signals

Wireless, networks, machine learning

PI
Core/Dual

Charles E. Leiserson

Professor

Algorithms, parallel computing

E cel@csail.mit.edu

T 253-5833

Lead

Supertech Research Group

Performance Engineering of Cache Profilers

CilkPride

A Simplified and Extensible Cilk Runtime for Research

Member

Bellmania

Algorithms, parallel computing

Lucas Liebenwein

Graduate Student

Student and Researcher | Robotics, AI | Advanced Autonomy

E lucasl@mit.edu

RM 32-376C

Lead

Safety Standards for Autonomous Vehicles

Member

Self-Driving Vehicles

Coresets for Machine Learning Algorithms

Student and Researcher | Robotics, AI | Advanced Autonomy

Andrea Lincoln

Graduate Student

E andreali@mit.edu

Andrew Lo

Professor

Financial engineering, risk management, data science

E alo@mit.edu

T 253-0920

Financial engineering, risk management, data science

Zelda Mariet

Graduate Student

E zelda@csail.mit.edu

PI
Core/Dual

Ankur Moitra

Associate Professor

Theory, algorithms, machine learning, complexity

E moitra@csail.mit.edu

T 253-5876

Lead

Efficient Robust Estimation in High Dimensions

Theory, algorithms, machine learning, complexity

PI
Core/Dual

Ronald Rivest

Institute Professor

Cryptography, cybersecurity, RSA public-key encryption

E rivest@mit.edu

T 253-5880

Lead

Member

Keys Under Doormats

Cryptography, cybersecurity, RSA public-key encryption

PI
Core/Dual

Ronitt Rubinfeld

Professor

Theory, algorithms

E ronitt@csail.mit.edu

T 253-0884

Lead

Complexity Theory Group

Sublinear/Streaming Algorithms for Covering Problem

Theory, algorithms

Nicholas Schiefer

Graduate Student

E schiefer@mit.edu

PI
Core/Dual

Julian Shun

Assistant Professor

Parallel computing, applied algorithms, graph processing.

E jshun@mit.edu

T 258-0669

Lead

Compression and Reordering for Parallel Graph Analytics

Programming Abstractions for Dynamic Graph Analytics

Bridging Theory and Practice in Shared-Memory Parallel Algorithm Design

Parallel computing, applied algorithms, graph processing.

11 News Results matching all criteria

Algorithms & Theory Systems & Networking Health Care

May 15 '18

Removing health-care barriers and boundaries

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

Removing health-care barriers and boundaries

Algorithms & Theory AI & Machine Learning Big Data

April 26 '18

Building AI systems that make fair decisions

Harini Suresh, a PhD student at MIT CSAIL, studies how to make machine learning algorithms more understandable and less biased.

Building AI systems that make fair decisions

Algorithms & Theory

March 22 '18

CSAIL’s Tom Leighton receives Marconi Prize, top prize in communications technology

Algorithms & Theory Robotics Energy Manufacturing Transportation

February 12 '18

Programming drones to fly in the face of uncertainty

CSAIL's NanoMap system enables drones to avoid obstacles while flying at 20 miles per hour, by more deeply integrating sensing and control.

Programming drones to fly in the face of uncertainty

Algorithms & Theory AI & Machine Learning

February 07 '18

Institute launches the MIT Intelligence Quest

New Institute-wide initiative will advance human and machine intelligence research.

Institute launches the MIT Intelligence Quest

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

January 16 '18

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

Professor Berthold Horn and postdoctoral associate Liang Wang

Algorithms & Theory Graphics & Vision Transportation

December 14 '17

Improving traffic - by tailgating less

New CSAIL work shows that traffic would flow faster if drivers kept an equal distance between cars

Improving traffic - by tailgating less

Algorithms & Theory Robotics Security & Cryptography Cybersecurity Internet of Things Manufacturing

December 11 '17

Four from MIT named 2017 Association for Computer Machinery Fellows

Today four MIT faculty were named among the Association for Computer Machinery's 2017 Fellows for making “landmark contributions to computing.”

Four from MIT named 2017 Association for Computer Machinery Fellows

Algorithms & Theory Programming Languages & Software Systems & Networking Cybersecurity

December 11 '17

Goldwasser gives briefing on cryptography to Congress

Last week CSAIL principal investigator Shafi Goldwasser spoke about cryptography and privacy as part of the annual congressional briefing of the American Mathematical Society (AMS) and the Mathematical Sciences Research Institute (MSRI).

Goldwasser gives briefing on cryptography to Congress

Daniel Jackson was awarded the Outstanding Research Award and Impact Paper Award (photo credit Sharona Jacobs)

Algorithms & Theory AI & Machine Learning Big Data Cybersecurity

June 02 '17

CSAIL's Daniel Jackson receives two ACM awards

This week the Association for Computer Machinery presented CSAIL principal investigator Daniel Jackson with the 2017 ACM SIGSOFT Outstanding Research Award for his pioneering work in software engineering. (This fall he also received the ACM SIGSOFT Impact Paper Award for his research method for finding bugs in code.)An EECS professor and associate director of CSAIL, Jackson was given the Outstanding Research Award for his “foundational contributions to software modeling, the creation of the modeling language Alloy, and the development of a widely used tool supporting model verification.”

CSAIL's Daniel Jackson receives two ACM awards

System directs camera-equipped drones to maintain framing of an aerial shot.

Algorithms & Theory AI & Machine Learning Graphics & Vision Robotics Entertainment Transportation

May 17 '17

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

14 Group Results

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

Complexity Theory Group

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

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

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.

+10

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

+10

Research Group

Geometric Data Processing Group

Our group studies geometric problems in computer graphics, computer vision, machine learning, optimization, and other disciplines.

Justin Solomon

Leads

Justin Solomon

Research Areas

Impact Areas

Lead

Justin Solomon

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

Lecturers

Lecturers in CSAIL

Debayan Gupta

Leads

Debayan Gupta

Research Areas

Impact Areas

Lead

Debayan Gupta

Research Group

Multicore Algorithmics

Nir Shavit

Leads

Nir Shavit

Research Areas

Impact Areas

Lead

Nir Shavit

Research Group

Multimodal Understanding Group

Our objective is to build techniques, software, and hardware that enable natural interaction with
computation.

Randall Davis

Leads

Randall Davis

Research Areas

Impact Areas

Lead

Randall Davis

Research Group

Quantum Information Science Group

Our research interests center around the capabilities and limits of quantum computers, and computational complexity theory more generally.

Peter Shor

Leads

Peter Shor

Research Areas

Impact Areas

Lead

Peter Shor

Research Group

Supertech Research Group

We investigate the technologies that support scalable high-performance computing, including hardware, software, and theory.

Charles E. Leiserson

Leads

Charles E. Leiserson

Research Areas

Computer Architecture

Impact Areas

Lead

Charles E. Leiserson

Research Group

Theory of Computation Group

Theory research at CSAIL covers a broad spectrum of topics, including algorithms, complexity theory, cryptography, distributed systems, parallel computing and quantum computing.

Leads

Bonnie Berger

Costis Daskalakis

Erik Demaine

Alan Edelman

Michael Goemans

Shafi Goldwasser

Piotr Indyk

David Karger

Jonathan Kelner

Tom Leighton

Charles E. Leiserson

Nancy Lynch

Aleksander Madry

Albert R. Meyer

Silvio Micali

Ankur Moitra

Ronald Rivest

Ronitt Rubinfeld

Nir Shavit

Peter Shor

Vinod Vaikuntanathan

Ryan Williams

Virginia Vassilevska Williams

Research Areas

Impact Areas

Lead

Bonnie Berger

Costis Daskalakis

Erik Demaine

Alan Edelman

Michael Goemans

Shafi Goldwasser

Piotr Indyk

David Karger

Jonathan Kelner

Tom Leighton

Charles E. Leiserson

Nancy Lynch

Aleksander Madry

Albert R. Meyer

Silvio Micali

Ankur Moitra

Ronald Rivest

Ronitt Rubinfeld

Nir Shavit

Peter Shor

Vinod Vaikuntanathan

Ryan Williams

Virginia Vassilevska Williams

Research Group

Theory of Distributed Systems Group

Nancy Lynch

Leads

Nancy Lynch

Research Areas

Impact Areas

Lead

Nancy Lynch

47 Project Results

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

Charles E. Leiserson

Tao Schardl

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.

Josh Alman

Virginia Vassilevska Williams

Leads

Josh Alman

Virginia Vassilevska Williams

Research Areas

Josh Alman

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

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

Virginia Vassilevska Williams

Project

Aspect-Augmented Adversarial Networks for Domain Adaptation

Regina Barzilay

Tommi Jaakkola

Leads

Regina Barzilay

Tommi Jaakkola

Research Areas

Regina Barzilay

Tommi Jaakkola

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

Leads

Itay Berman

Akshay Degwekar

Ron Rothblum

Prashant Vasudevan

Research Areas

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

Coresets for Machine Learning Algorithms

Our goal is to design novel data compression techniques to accelerate popular machine learning algorithms in Big Data and streaming settings.

Daniela Rus

Leads

Daniela Rus

Research Areas

Impact Areas

Daniela Rus

Project

Data Garbling: Computing on Encrypted Data

We are investigating the limits of computing on encrypted data, with a focus on the private outsourcing of computation over sensitive data.

Leads

Research Areas

Impact Areas

Project

Deep Inverse Planning

Deep inverse planning for learning from high-dimensional demonstrations

Leads

Research Areas

Learning and Intelligent Systems

Project

Deterministic Algorithms for Robotic Task and Motion Planning

Our goal is to investigate deterministic algorithms for robotic task and motion planning.

Ashwin Deshpande

Leads

Ashwin Deshpande

Research Areas

Theory of Distributed Systems Group

Impact Areas

Manufacturing

Transportation

Ashwin Deshpande

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

Nancy Lynch

Project

Distributed Robot Garden

The robot garden provides an aesthetically pleasing educational platform that can visualize computer science concepts and encourage young students to pursue programming and robotics.

Leads

Joseph DelPreto

Lindsay Sanneman

Daniela Rus

Research Areas

Impact Areas

Entertainment

Project

Diversity-inducing Probability Measures

Machine Learning

Leads

Chengtao Li

Stefanie Jegelka

Suvrit Sra

Research Areas

Impact Areas

Project

Driver-Friendly Bilateral Control for Suppressing Traffic Instabilities

Self-driving cars themselves can solve traffic problems even without global control.

Leads

Research Areas

Project

Efficient Robust Estimation in High Dimensions

We are developing robust estimators for multivariate distributions which are both computationally efficient and near-optimal in terms of their accuracy. Our focus is on methods which are both theoretically sound and practically effective.

Leads

Gautam Kamath

Jerry Li

Ankur Moitra

Research Areas

Project

Fast Lightweight Autonomy

The goal of the FLA program is to explore non-traditional perception and autonomy methods that could enable a new class of algorithms for minimalistic high-speed navigation in cluttered environments.

John Carter

Jake Ware

Leads

John Carter

Jake Ware

Research Areas

John Carter

Jake Ware

Project

Generating Good Adversarial Examples for Neural Networks

Robot Locomotion Group

Leads

Research Areas

Data-Driven Inference Group

Project

Hidden Influencers, Risk and Causes of Infection

We aim to study the causes and transmission modes of infectious diseases among members of a community in the presence of hidden, asymptomatic spreaders of the pathogen.

Maggie Makar

John Guttag

Leads

Maggie Makar

John Guttag

Research Areas

Impact Areas

Maggie Makar

John Guttag

Project

Is the Casino using a Riffle Shuffle?