Research

Impact Areas

Lead

Martin Rinard

17 Group Results

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 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

Robotics

Impact Areas

Lead

Aleksander Madry

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

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

Lead

David Karger

Lea Verou

David Karger

Research Center

Internet Policy Research Initiative

Our mission is to work with policy makers and cybersecurity technologists to increase the trustworthiness and effectiveness of interconnected digital systems.

Leads

Daniel Weitzner

Hal Abelson

David Clark

Lalana Kagal

Karen Sollins

Gerald Sussman

Research Areas

Impact Areas

Lead

Daniel Weitzner

Hal Abelson

David Clark

Lalana Kagal

Karen Sollins

Gerald Sussman

Research Group

MIT App Inventor

MIT App Inventor is an intuitive, visual programming environment that allows everyone – even children – to build fully functional apps for smartphones and tablets.

Hal Abelson

Leads

Hal Abelson

Research Areas

Impact Areas

Lead

Hal Abelson

Research Group

Programming Methodology Group

We develop innovative approaches for building software and for solving problems in modern parallel and distributed software systems.

Barbara Liskov

Leads

Barbara Liskov

Research Areas

Impact Areas

Lead

Barbara Liskov

Research Group

Sensing, Learning and Inference

We develop scalable algorithms for analysis of complex, high-dimensional data.

John Fisher

Leads

John Fisher

Research Areas

Robotics

Impact Areas

Energy

Lead

John Fisher

Research Group

Software Design Group

Our goal is to find better ways to make software, and ways to make software better.

Daniel Jackson

Leads

Daniel Jackson

Research Areas

Impact Areas

Lead

Daniel Jackson

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

Impact Areas

Lead

Charles E. Leiserson

Neil Thompson

Charles E. Leiserson

Neil Thompson

Community of Research

Systems Community of Research

The Systems CoR is focused on building and investigating large-scale software systems that power modern computers, phones, data centers, and networks, including operating systems, the Internet, wireless networks, databases, and other software infrastructure.

+21

Sam Madden

Leads

Sam Madden

Research Areas

Impact Areas

Lead

Sam Madden

+21

Sam Madden

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

Computational Biology

Impact Areas

Lead

Costis Daskalakis

+20

Costis Daskalakis

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

Research Group

Visualization Group

We use visualization as a petri dish to study intelligence augmentation, or how can computational representations and software systems help amplify our cognition and creativity, while respecting our agency?

Arvind Satyanarayan

Leads

Arvind Satyanarayan

Research Areas

Impact Areas

Human-Computer Interaction Community of Research

Lead

Arvind Satyanarayan

21 Project Results

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

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

Compression and Reordering for Parallel Graph Analytics

We plan to develop a suite of graph compression and reordering techniques as part of the Ligra parallel graph processing framework to reduce space usage and improve performance of graph algorithms.

Leads

Research Areas

Impact Areas

Computational Design and Fabrication Group

Project

Crowdsourcing in Graphics and Vision

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

Alexandre Kaspar

Leads

Alexandre Kaspar

Research Areas

Impact Areas

Entertainment

Alexandre Kaspar

Project

Data Civilizer

Data scientists universally report that they spend at least 80% of their time finding data sets of interest, accessing them, cleaning them and assembling them into a unified whole.

Michael Stonebraker

Sam Madden

Leads

Michael Stonebraker

Sam Madden

Research Areas

Impact Areas

Michael Stonebraker

Sam Madden

Project

Data Warehouse Construction

Historically, DBMSs in the warehouse space partitioned their data across a shared nothing
cluster.

Michael Stonebraker

Leads

Michael Stonebraker

Research Areas

Impact Areas

Michael Stonebraker

Project

Database Design

The conventional wisdom described in all text books for performing database design is never followed in practice.

Michael Stonebraker

Leads

Michael Stonebraker

Research Areas

Impact Areas

Michael Stonebraker

Project

Determining Wikipedia's Influence on Science

Supertech Research Group

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

Geometry and topology for scientific computing and shape analysis

Computer Graphics Group

Developing state-of-the-art tools that process 3D surfaces and volumes

Justin Solomon

Leads

Justin Solomon

Research Areas

Impact Areas

Health Care

Justin Solomon

Project

Geometry in Large-Scale Machine Learning

Machine Learning

Data often has geometric structure which can enable better inference; this project aims to scale up geometry-aware techniques for use in machine learning settings with lots of data, so that this structure may be utilized in practice.

Justin Solomon

Stefanie Jegelka

Leads

Justin Solomon

Stefanie Jegelka

Research Areas

Impact Areas

Justin Solomon

Stefanie Jegelka

Project

High-Performance Parallel Clustering

We are designing new parallel algorithms, optimizations, and frameworks for clustering large-scale graph and geometric data.

Julian Shun

Leads

Julian Shun

Research Areas

Impact Areas

Julian Shun

Project

Political Geometry: Establishing Fair Mathematical Standards for Political Redistricting

Gerrymandering is a direct threat to our democracy, undermining founding principles like equal protection under the law and eroding public confidence in elections.

Justin Solomon

Leads

Justin Solomon

Research Areas

Impact Areas

Decentralized Information Group

Justin Solomon

Project

PrivacyML - A Privacy Preserving Framework for Machine Learning

We are developing a general framework that enforces privacy transparently enabling different kinds of machine learning to be developed that are automatically privacy preserving.

Lalana Kagal

Vaikkunth Mugunthan

Leads

Lalana Kagal

Vaikkunth Mugunthan

Research Areas

Programming Systems Group

Impact Areas

Lalana Kagal

Vaikkunth Mugunthan

Project

Program Performance Prediction with Deep Learning

Commit Group

Predicting the number of clock cycles a processor takes to execute a block of assembly instructions in steady-state (the throughput) is important for both compiler designers and performance engineers.

However, building an analytical model to do so is especially complicated in modern x86-64 Complex Instruction Set Computer (CISC) machines with sophisticated processor microarchitectures in that it is tedious, error-prone, and must be performed from scratch for each processor generation.

Ithemal is the first tool that learns to predict the throughput of a set of instructions. It does so more accurately than state-of-the-art hand-written tools currently used in compiler backends and static machine code analyzers. In particular, Ithemal has less than half the error of state-of-the-art analytical models (LLVM's llvm-mca and Intel's IACA).

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

Model-Based Embedded and Robotics Systems Group

Julian Shun

Project

Securing IoT

IoT devices primarily use free embedded Linux which has many security flaws. We are conducting penetration tests on IoT and developing a secure version of embedded Linux.

Howard Shrobe

Leads

Howard Shrobe

Research Areas

Impact Areas

Howard Shrobe

Project

Sensible Deep Learning for 3D Data

Machine Learning

Developing state-of-the-art deep learning algorithms for analyzing and modeling 3D geometry

Justin Solomon

Leads

Justin Solomon

Research Areas

Impact Areas

Decentralized Information Group

Manufacturing

Justin Solomon

Project

Solid: Social Linked Data

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

Health Care

Tim Berners-Lee

Lalana Kagal

Project

Starling: Query Optimization for Cloud Services

Starling is a scalable query execution engine built on cloud function services that computes at a fine granularity, helping people more easily match workload demand.

Sam Madden

Matthew Perron

Leads

Sam Madden

Matthew Perron

Research Areas

Impact Areas

Wireless

Sam Madden

Matthew Perron

Project

Tiramisu Compiler

Commit Group

A polyhedral compiler for expressing image processing, DNN, and linear/tensor algebra applications

Saman Amarasinghe

Leads

Saman Amarasinghe

Research Areas

Impact Areas

Saman Amarasinghe

Project

Video Data Querying

We are developing machine-learning technology to help users efficiently run data queries over large archives of raw video.

Sam Madden

Favyen Bastani

Leads

Sam Madden

Favyen Bastani

Research Areas

Impact Areas

Simit: A Language for Computing on Sparse Systems

Entertainment

Transportation

Sam Madden

Favyen Bastani

30 People Results

PI
Core/Dual

Saman Amarasinghe

Professor

Compilers, architectures, software engineering

E saman@csail.mit.edu

T 253-8879

Lead

Commit Group

Tiramisu Compiler

Member

Taco: The Tensor Algebra Compiler

Halide

OpenTuner: An Extensible Framework for Program Autotuning

Program Performance Prediction with Deep Learning

Natural Language Processing Group

Compilers, architectures, software engineering

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

Programming Systems Group

Natural language processing, machine learning

PI
Core/Dual

Michael Carbin

Assistant Professor

Programming languages and systems.

E mcarbin@csail.mit.edu

T 253-5881

Lead

The Lottery Ticket Hypothesis

Member

Programming with spaces

Program Performance Prediction with Deep Learning

Unsupervised Speech Processing

Programming languages and systems.

Yu-An Chung

Graduate Student

Speech and language processing, machine learning

E andyyuan@mit.edu

Lead

Member

Spoken Language Systems Group

Speech and language processing, machine learning

PI
Core/Dual

David Clark

Senior Research Scientist

Internet architectures, communications policy, security

E ddc@csail.mit.edu

T 253-6003

Lead

Advanced Network Architecture Group

Internet Policy Research Initiative

Member

Sensing, Learning and Inference

Internet architectures, communications policy, security

Mustafa Doga Dogan

Graduate Student

E doga@mit.edu

Member

HCI Engineering Group

R. David Edelman

Director, Project on Technology, Economy & National Security

Machine learning, cybersecurity, governance

E rde@mit.edu

T 258-6389

Machine learning, cybersecurity, governance

Gregory Falco

Research Affiliate

Dr. Falco is a hacker and expert in IoT and IIoT cybersecurity.

E gfalco@mit.edu

Dr. Falco is a hacker and expert in IoT and IIoT cybersecurity.

PI
Core/Dual

John Fisher

Senior Research Scientist

Vision, machine learning, signal processing

E fisher@csail.mit.edu

T 253-0788

Lead

Vision Group

Member

Visual Computing Community of Research

Vision, machine learning, signal processing

Evan Hernandez

Graduate Student

Natural language processing, machine learning, interpretability

E dez@mit.edu

Natural language processing, machine learning, interpretability

Jamey Hicks

Research Affiliate

E jamey.hicks@accelerated.tech

Member

Computation Structures Group

PI
Core/Dual

Daniel Jackson

Professor

Software design, programming, systems

E dnj@csail.mit.edu

T 258-8471

Lead

Rethinking Software Design

Software Design Group

Gitless: a simple version control system built on top of Git

Déjà Vu: Constructing Apps from Concepts

Security by Design for Cyberphysical Systems

Poirot: Secure Protocol Implementation by Design

An Interlock for Self Driving Cars

Alloy

Wildcard

Member

Espalier

Human-Computer Interaction Community of Research

Parallel and Distributed Operating Systems

Wildcard

Software design, programming, systems

PI
Core/Dual

Frans Kaashoek

Professor

Systems, networks, architectures

E kaashoek@csail.mit.edu

T 253-7149

Lead

Scaling Filesystems To Many Cores

Perennial

Member

Noria: a new data-flow system for web applications

Computation Structures Group

FSCQ: File-system verification

Embodied Intelligence Community of Research

Systems, networks, architectures

PI
Core/Dual

John Leonard

Professor

Robotics, navigation/mapping, self-driving cars

E jleonard@csail.mit.edu

T 253-5305

Lead

Marine Robotics Group

Self-Driving Vehicles

Member

Robotics, navigation/mapping, self-driving cars

Henry Lieberman

Research Scientist

Henry Lieberman is a Research Scientist at MIT CSAIL, in AI and HCI.

E lieber@MEDIA.MIT.EDU

Henry Lieberman is a Research Scientist at MIT CSAIL, in AI and HCI.

Vaikkunth Mugunthan

Graduate Student

Privacy and Big Data

E vaik@mit.edu

Lead

PrivacyML - A Privacy Preserving Framework for Machine Learning

Member

Decentralized Information Group

Privacy and Big Data

PI
Core/Dual

Una-May O'Reilly

Principal Research Scientist

Applied AI and ML in cybersecurity, healthcare, education

E unamay@csail.mit.edu

T 253-6437

Lead

Anyscale Learning for All ALFA

Adversarial Cyber Security

GIGABEATS: Data science for medical sensor data

MOOC Learner Project: Data science for e-learning

Member

Distributed Robotics Laboratory

Applied AI and ML in cybersecurity, healthcare, education

PI
Core/Dual

Daniela Rus

Director

CSAIL director, robotics, AI, data science, privacy

E rus@csail.mit.edu

T 258-7567

RM 32/ 32-368/ 374

Lead

Social Network Extraction from GPS Datasets with Coresets

Safety Standards for Autonomous Vehicles

Soft Contact Modeling

Practical Secure Computation

Self-Driving Vehicles

Robust Learning for Autonomous Vehicles

Brain-Controlled Robots

Planning in Congestion for Autonomous Vehicles

Socially-Compliant Behavior for Autonomous Driving

Coresets for Machine Learning Algorithms

M-Blocks Modular Robotics

Robot Compiler

Distributed Robot Garden

Route and Motion Planning for Mobility-on-Demand with Rules of the Road

Member

Social Network Extraction from GPS Datasets with Coresets

Task-Driven Co-Optimization Of Articulated Robots

Wearable Blind Navigation

Drones that Drive

Better Models for Ride-Sharing

SoFi - The Soft Robotic Fish

Controlling drones and other robots with gestures

Using Muscle Signals to Lift Objects with Robots

Embodied Intelligence Community of Research

Helping robots learn using demonstrations

CSAIL director, robotics, AI, data science, privacy

PI
Core/Dual

Arvind Satyanarayan

Assistant Professor

E arvindsatya@mit.edu

Lead

Visualization Group

Member

Center for Deployable Machine Learning (CDML)

Human-Computer Interaction Community of Research

PI
Core/Dual

Julian Shun

Assistant Professor

Parallel computing, applied algorithms, graph processing.

E jshun@mit.edu

T 258-0669

Lead

Programming Abstractions for Dynamic Graph Analytics

Bridging Theory and Practice in Shared-Memory Parallel Algorithm Design

High-Performance Parallel Clustering

Member

Theory of Computation Community of Research

Parallel computing, applied algorithms, graph processing.

Dmitriy Smirnov

Graduate Student

https://people.csail.mit.edu/smirnov/

E smirnov@mit.edu

RM 32-D475B

Member

Sensible Deep Learning for 3D Data

https://people.csail.mit.edu/smirnov/

PI
Core/Dual

Armando Solar-Lezama

Associate Professor

Programming languages, software analysis

E asolar@csail.mit.edu

T 258-9727

Lead

Computation Structures Group

Synquid: Synthesis From Liquid Types

Computer-Aided Programming

An Interlock for Self Driving Cars

Member

Center for Deployable Machine Learning (CDML)

Programming languages, software analysis

PI
Core/Dual

Justin Solomon

Assistant Professor

Geometry, graphics, vision, machine learning, optimization.

E jsolomon@mit.edu

Lead

Computer Graphics Group

Geometry in Large-Scale Machine Learning

Political Geometry: Establishing Fair Mathematical Standards for Political Redistricting

Sensible Deep Learning for 3D Data

Optimal transport for statistics and machine learning

Geometry and topology for scientific computing and shape analysis

Member

Visual Computing Community of Research

Geometry, graphics, vision, machine learning, optimization.

PI
Core/Dual

Gerald Sussman

Professor

Artificial intelligence, supercomputers

E gjs@csail.mit.edu

T 253-5874

RM 32/ 32-G508/ G514

Lead

Sussman Lab

The Car Can Explain!

Internet Policy Research Initiative

Member