Research

Impact Areas

Lead

Lalana Kagal

Tim Berners-Lee

Lalana Kagal

Tim Berners-Lee

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

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

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

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

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

Neil Thompson

Leads

Charles E. Leiserson

Neil Thompson

Research Areas

Computer Architecture

Impact Areas

Lead

Charles E. Leiserson

Neil Thompson

Charles E. Leiserson

Neil Thompson

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

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

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

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

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

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

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

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 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

Lecturers

Lecturers in CSAIL

Leads

Research Areas

Impact Areas

Community of Research

Theory of Computation Community of Research

The goal of the Theory of Computation CoR is to study the fundamental strengths and limits of computation as well as how these interact with mathematics, computer science, and other disciplines.

+20

Costis Daskalakis

Leads

Costis Daskalakis

Research Areas

Impact Areas

Lead

Costis Daskalakis

+20

Costis Daskalakis

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

Community of Research

Vertical AI Community of Research

This CoR takes a unified approach to cover the full range of research areas required for success in artificial intelligence, including hardware, foundations, software systems, and applications.

Martin Rinard

Leads

Martin Rinard

Research Areas

Impact Areas

Lead

Martin Rinard

62 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

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

Deep Inverse Planning

Vision Group

Deep inverse planning for learning from high-dimensional demonstrations

Leads

Research Areas

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

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

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

Yuening Zhang

Brian Williams

Howard Shrobe

Research Areas

Impact Areas

Manufacturing

Project

Bayesian Optimization for Global Optimization of Expensive Black-box Functions

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.

Leads

Research Areas

Impact Areas

Project

Active Learning of Models for Planning

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

Reconstructing Neural Circuits from Mammalian Brain

We develop algorithms, systems and software architectures for automating reconstruction of accurate representations of neural tissue structures, such as nanometer-scale neurons' morphology and synaptic connections in the mammalian cortex.

Yaron Meirovitch

Nir Shavit

Leads

Yaron Meirovitch

Nir Shavit

Research Areas

Impact Areas

Yaron Meirovitch

Nir Shavit

Project

Performance Engineering of Cache Profilers

Our goal is to develop lightweight tools that allow programmers to better understand the cache performance of their applications. Tasks include designing profilers, performance engineering existing ones, and exploring different metrics for cache interactions.

Helen Xu

Charles E. Leiserson

Leads

Helen Xu

Charles E. Leiserson

Research Areas

Helen Xu

Charles E. Leiserson

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

Project

Deterministic Algorithms for Robotic Task and Motion Planning

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

Leads

Research Areas

Impact Areas

Manufacturing

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

Data-Driven Inference Group

Maggie Makar

John Guttag

Project

Predicting Adverse Events Across Changing Electronic Health Record Systems

Cognitive AI Community of Research

Applied Machine Learning Community of Research

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

John Guttag

Peter Szolovits

Leads

John Guttag

Peter Szolovits

Research Areas

Impact Areas

John Guttag

Peter Szolovits

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

Wilko Schwarting

Daniela Rus

Research Areas

Impact Areas

Project

Algorithmic Aspects of Performance Engineering

The project concerns algorithmic solutions for writing fast codes.

Leads

Research Areas

Impact Areas

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

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.

Ankur Moitra

Leads

Ankur Moitra

Research Areas

Ankur Moitra

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

Project

Drones that Drive

Multi-robot path planning for robot swarms that can both fly and drive

Leads

Research Areas

Impact Areas

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

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

40 People Results matching all criteria

Leandro Agudelo

Research Scientist

Systems Genomics, CompBio, Topological Integrative Biology, Biology

E lagudelo@csail.mit.edu

Systems Genomics, CompBio, Topological Integrative Biology, Biology

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

Applied Machine Learning Community of Research

Natural language processing, machine learning

Cenk Baykal

Graduate Student

E baykal@mit.edu

RM 32-376C

Member

PI
Core/Dual

Costis Daskalakis

Associate Professor

Algorithms, Economics, Game Theory, Statistics, Machine Learning

E costis@csail.mit.edu

T 253-9643

Lead

Is the Casino using a Riffle Shuffle?

Understanding Convergence of Iterative Algorithms

Member

Algorithms, Economics, Game Theory, Statistics, Machine Learning

PI
Core/Dual

Erik Demaine

Professor

Algorithms, theory, computational geometry, complexity

E edemaine@mit.edu

T 253-6871

Lead

Member

Algorithms, theory, computational geometry, complexity

Martin Demaine

Robotics Engineer

E mdemaine@mit.edu

T 253-7953

Barış Ekim

Graduate Student

E ekim@csail.mit.edu

PI
Core/Dual

Shafi Goldwasser

Professor

Theory, cryptography, cybersecurity, complexity

E shafi@csail.mit.edu

T 253-5914

Lead

Complexity Theory Group

Member

Theory, cryptography, cybersecurity, complexity

Noah Golowich

Graduate Student

E nzg@mit.edu

RM 32-G585B

Joanne Hanley

Administrative Assistant II

Administrative Assistant, Theory of Computation

E joanne@csail.mit.edu

T 253-6054

Member

Administrative Assistant, Theory of Computation

Dhiraj Holden

Graduate Student

E dholden@mit.edu

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

Member

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

Aspect-Augmented Adversarial Networks for Domain Adaptation

Learning Strategic Games

Structured Prediction Through Randomization

Interpretability in complex machine learning models

Member

Learning Optimal Interventions

Machine learning, natural language processing, genomics

Siddhartha Jayanti

Graduate Student

E siddhartha@csail.mit.edu

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

Talkademic: Motivating Online Academic Discourse

Member

Human-Computer Interaction Community of Research

EQ-Radio: Emotion Recognition using Wireless Signals

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

Member

Wireless, networks, machine learning

William Kuszmaul

Graduate Student

Research interests in algorithms and high-performance engineering

E kuszmaul@mit.edu

Research interests in algorithms and high-performance engineering

PI
Core/Dual

Charles E. Leiserson

Professor

Algorithms, parallel computing, performance engineering

E cel@csail.mit.edu

T 253-5833

Lead

Performance Engineering of Cache Profilers

CilkPride

A Simplified and Extensible Cilk Runtime for Research

Determining Wikipedia's Influence on Science

Tapir

Member

Safety Standards for Autonomous Vehicles

Algorithms, parallel computing, performance engineering

Lucas Liebenwein

Graduate Student

Student and Researcher | Robotics, AI | Advanced Autonomy

E lucasl@mit.edu

RM 32-376C

Lead

Member

Self-Driving Vehicles

Student and Researcher | Robotics, AI | Advanced Autonomy

PI
Core/Dual

Aleksander Madry

Associate Professor

Theory, algorithms, optimization, robust and reliable ML

E madry@mit.edu

T 324-6739

Lead

Reliable and Robust Machine Learning

Member

Theory, algorithms, optimization, robust and reliable ML

PI
Core/Dual

Albert R. Meyer

Professor Emeritus

Programming languages, theory, complexity, online education

E meyer@csail.mit.edu

T 253-6024

Programming languages, theory, complexity, online education

Slobodan Mitrovic

Postdoctoral Associate

E slobo@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

Member

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

Computing & Society Community of Research

Cryptography, cybersecurity, RSA public-key encryption

85 News Results matching all criteria

Algorithms & Theory Programming Languages & Software Engineering Systems & Networking

February 22 '21

Researchers develop speedier network analysis for a range of computer hardware

The advance could boost recommendation algorithms and internet search.

Researchers develop speedier network analysis for a range of computer hardware

Algorithms & Theory AI & ML

January 28 '21

“Liquid” machine-learning system adapts to changing conditions

The new type of neural network could aid decision making in autonomous driving and medical diagnosis.

“Liquid” machine-learning system adapts to changing conditions

Algorithms & Theory AI & ML Computational Biology Health Care

January 27 '21

Robust AI tools to predict future cancer

Researchers created a risk-assessment algorithm that shows consistent performance across datasets from US, Europe and Asia.

Robust AI tools to predict future cancer

Algorithms & Theory AI & ML Robotics

January 22 '21

Designing customized “brains” for robots

A new system devises hardware architectures to hasten robots’ response time.

Designing customized “brains” for robots

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

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

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

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

Algorithms & Theory AI & ML Health Care

September 17 '20

Monitoring sleep positions for a healthy rest

Wireless device captures sleep data without using cameras or body sensors; could aid patients with Parkinson’s disease, epilepsy, or bedsores.

Monitoring sleep positions for a healthy rest

Algorithms & Theory AI & ML Programming Languages & Software Engineering

September 08 '20

Toward a machine learning model that can reason about everyday actions

Researchers train a model to reach human-level performance at recognizing abstract concepts in video.

Toward a machine learning model that can reason about everyday actions

Algorithms & Theory Programming Languages & Software Engineering Energy

August 12 '20

Shrinking deep learning’s carbon footprint

Through innovation in software and hardware, researchers move to reduce the financial and environmental costs of modern artificial intelligence.

Shrinking deep learning’s carbon footprint

Algorithms & Theory Systems & Networking

July 29 '20

Looking into the black box

Recent advances give theoretical insight into why deep learning networks are successful.

Looking into the black box

Algorithms & Theory Entertainment

July 29 '20

Algorithm finds hidden connections between paintings at the Met

A team from MIT helped create an image retrieval system to find the closest matches of paintings from different artists and cultures.

Algorithm finds hidden connections between paintings at the Met

Algorithms & Theory Robotics

June 02 '20

New glove lets you incorporate real-life objects into virtual worlds

Algorithms & Theory Robotics Manufacturing

June 01 '20

Giving soft robots senses

In a pair of papers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), two teams enable better sense and perception for soft robotic grippers.

Giving soft robots senses

Algorithms & Theory Programming Languages & Software Engineering

May 06 '20

Visualizing the world beyond the frame

Researchers test how far artificial intelligence models can go in dreaming up varied poses and colors of objects and animals in photos.

Visualizing the world beyond the frame

Algorithms & Theory

April 28 '20

Automating the search for entirely new “curiosity” algorithms

Researchers show that computers can “write” algorithms that adapt to radically different environments better than algorithms designed by humans.

Automating the search for entirely new “curiosity” algorithms

Algorithms & Theory AI & ML Health Care Wireless

April 14 '20

CSAIL device lets doctors monitor COVID-19 patients from a distance

Wireless system helps Boston retirement home care for COVID patients while reducing risk of contagion

CSAIL device lets doctors monitor COVID-19 patients from a distance

Algorithms & Theory

March 24 '20

System trains driverless cars in simulation before they hit the road

Using a photorealistic simulation engine, vehicles learn to drive in the real world and recover from near-crash scenarios.

System trains driverless cars in simulation before they hit the road

Algorithms & Theory AI & ML

March 16 '20

“Doing machine learning the right way”

Professor Aleksander Madry strives to build machine-learning models that are more reliable, understandable, and robust.

“Doing machine learning the right way”

Algorithms & Theory AI & ML Robotics

March 05 '20

Showing robots how to do your chores

By observing humans, robots learn to perform complex tasks, such as setting a table.

Showing robots how to do your chores

Algorithms & Theory Cybersecurity

February 26 '20

Protecting sensitive metadata so it can’t be used for surveillance

System ensures hackers eavesdropping on large networks can’t find out who’s communicating and when they’re doing so.

Protecting sensitive metadata so it can’t be used for surveillance

Automated system can rewrite outdated sentences in Wikipedia articles 1

Algorithms & Theory AI & ML

February 13 '20

Automated system can rewrite outdated sentences in Wikipedia articles

Text-generating tool pinpoints and replaces specific information in sentences while retaining humanlike grammar and style.

Automated system can rewrite outdated sentences in Wikipedia articles

20 Group Results

Research Group

Algorithms Group

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

Leads

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

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

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 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

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

Community of Research

Computing & Society Community of Research

Daniel Weitzner

Leads

Daniel Weitzner

Research Areas

Impact Areas

Lead

Daniel Weitzner

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

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

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

Leads

Research Areas

Impact Areas

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

Neil Thompson

Leads

Charles E. Leiserson

Neil Thompson

Research Areas

Computer Architecture

Impact Areas

Lead

Charles E. Leiserson

Neil Thompson

Charles E. Leiserson

Neil Thompson

Community of Research

Theory of Computation Community of Research

The goal of the Theory of Computation CoR is to study the fundamental strengths and limits of computation as well as how these interact with mathematics, computer science, and other disciplines.

+20

Costis Daskalakis

Leads

Costis Daskalakis

Research Areas

Impact Areas

Lead

Costis Daskalakis

+20

Costis Daskalakis

Research Group

Theory of Distributed Systems Group

Nancy Lynch

Leads

Nancy Lynch

Research Areas

Impact Areas

Lead

Nancy Lynch

Community of Research

Vertical AI Community of Research

This CoR takes a unified approach to cover the full range of research areas required for success in artificial intelligence, including hardware, foundations, software systems, and applications.

Martin Rinard

Leads

Martin Rinard

Research Areas

Impact Areas

Lead

Martin Rinard

62 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

Active Learning of Models for Planning

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

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

The project concerns algorithmic solutions for writing fast codes.

Leads

Research Areas

Impact Areas

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

Nancy Lynch

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

Research Areas

Project

Bayesian Optimization for Global Optimization of Expensive Black-box Functions

Leads

Research Areas

Impact Areas

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

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

Vision Group

Deep inverse planning for learning from high-dimensional demonstrations

Leads

Research Areas

Project

Determining Wikipedia's Influence on Science

Wikipedia is one of the most widely accessed encyclopedia sites in the world, including by scientists. Our project aims to investigate just how far Wikipedia’s influence goes in shaping science.

Neil Thompson

Charles E. Leiserson

Leads

Neil Thompson

Charles E. Leiserson

Research Areas

Impact Areas

Neil Thompson

Charles E. Leiserson

Project

Deterministic Algorithms for Robotic Task and Motion Planning

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

Leads

Research Areas

Impact Areas

Manufacturing

Project

Distributed Algorithms for Dynamic and Noisy Platforms

Distributed systems are now everywhere, for example, in wireless communication networks, distributed data-management systems, coordinated robots, transportation systems, and modern multiprocessors.

Nancy Lynch

Leads

Nancy Lynch

Research Areas

Nancy Lynch

Project

Distributed Co-prime Sampling Algorithms

To further parallelize co-prime sampling based sparse sensing, we introduce Diophantine Equation in different algebraic structures to build generalized lattice arrays.
With strong relationship to generalized Chinese Remainder Theorem, the geometry properties in the remainder code space, a special lattice space, are explored.

Hanshen Xiao

Leads

Hanshen Xiao

Research Areas

Impact Areas

Hanshen Xiao

Project

Distributed Computation in Ant Colonies

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

Project

Diversity-inducing Probability Measures

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.

Stefanie Jegelka

Suvrit Sra

Leads

Stefanie Jegelka

Suvrit Sra

Research Areas

Impact Areas

Stefanie Jegelka

Suvrit Sra

Project

Driver-Friendly Bilateral Control for Suppressing Traffic Instabilities

Vision Group

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

Leads

Research Areas

Project

Drones that Drive

Multi-robot path planning for robot swarms that can both fly and drive

Leads

Research Areas

Impact Areas

40 People Results

Leandro Agudelo

Research Scientist

Systems Genomics, CompBio, Topological Integrative Biology, Biology

E lagudelo@csail.mit.edu

Systems Genomics, CompBio, Topological Integrative Biology, Biology

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

Applied Machine Learning Community of Research

Natural language processing, machine learning

Cenk Baykal

Graduate Student

E baykal@mit.edu

RM 32-376C

Member

PI
Core/Dual

Costis Daskalakis

Associate Professor

Algorithms, Economics, Game Theory, Statistics, Machine Learning

E costis@csail.mit.edu

T 253-9643

Lead

Is the Casino using a Riffle Shuffle?

Understanding Convergence of Iterative Algorithms

Member

Algorithms, Economics, Game Theory, Statistics, Machine Learning

PI
Core/Dual

Erik Demaine

Professor

Algorithms, theory, computational geometry, complexity

E edemaine@mit.edu

T 253-6871

Lead

Member

Algorithms, theory, computational geometry, complexity

Martin Demaine

Robotics Engineer

E mdemaine@mit.edu

T 253-7953

Barış Ekim

Graduate Student

E ekim@csail.mit.edu

PI
Core/Dual

Shafi Goldwasser

Professor

Theory, cryptography, cybersecurity, complexity

E shafi@csail.mit.edu

T 253-5914

Lead

Complexity Theory Group

Member

Theory, cryptography, cybersecurity, complexity

Noah Golowich

Graduate Student

E nzg@mit.edu

RM 32-G585B

Joanne Hanley

Administrative Assistant II

Administrative Assistant, Theory of Computation

E joanne@csail.mit.edu

T 253-6054

Member

Administrative Assistant, Theory of Computation

Dhiraj Holden

Graduate Student

E dholden@mit.edu

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

Member

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

Aspect-Augmented Adversarial Networks for Domain Adaptation

Learning Strategic Games

Structured Prediction Through Randomization

Interpretability in complex machine learning models

Member

Learning Optimal Interventions

Machine learning, natural language processing, genomics

Siddhartha Jayanti

Graduate Student

E siddhartha@csail.mit.edu

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

Talkademic: Motivating Online Academic Discourse

Member

Human-Computer Interaction Community of Research

EQ-Radio: Emotion Recognition using Wireless Signals

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

Member

Wireless, networks, machine learning

William Kuszmaul

Graduate Student

Research interests in algorithms and high-performance engineering

E kuszmaul@mit.edu

Research interests in algorithms and high-performance engineering

PI
Core/Dual

Charles E. Leiserson

Professor

Algorithms, parallel computing, performance engineering

E cel@csail.mit.edu

T 253-5833

Lead

Performance Engineering of Cache Profilers

CilkPride

A Simplified and Extensible Cilk Runtime for Research

Determining Wikipedia's Influence on Science

Tapir

Member

Safety Standards for Autonomous Vehicles

Algorithms, parallel computing, performance engineering

Lucas Liebenwein

Graduate Student

Student and Researcher | Robotics, AI | Advanced Autonomy

E lucasl@mit.edu

RM 32-376C

Lead

Member

Self-Driving Vehicles

Student and Researcher | Robotics, AI | Advanced Autonomy

PI
Core/Dual

Aleksander Madry

Associate Professor

Theory, algorithms, optimization, robust and reliable ML

E madry@mit.edu

T 324-6739

Lead

Reliable and Robust Machine Learning

Member

Theory, algorithms, optimization, robust and reliable ML

PI
Core/Dual

Albert R. Meyer

Professor Emeritus

Programming languages, theory, complexity, online education

E meyer@csail.mit.edu

T 253-6024

Programming languages, theory, complexity, online education

Slobodan Mitrovic

Postdoctoral Associate

E slobo@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

Member

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