Research

Impact Areas

Lead

Una-May O'Reilly

Research Group

Broderick Lab

We work in the areas of statistics and machine learning.

Tamara Broderick

Leads

Tamara Broderick

Research Areas

Impact Areas

Lead

Tamara Broderick

Research 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

Cybersecurity

Lead

Aleksander Madry

Research Group

Computational Perception & Cognition

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

Aude Oliva

Leads

Aude Oliva

Research Areas

Computational Biology

Impact Areas

Lead

Aude Oliva

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

Data-Driven Inference Group

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

John Guttag

Leads

John Guttag

Research Areas

Impact Areas

Lead

John Guttag

Research Group

Decentralized Information Group

We are investigating decentralized technologies that affect social change.

Lalana Kagal

Tim Berners-Lee

Leads

Lalana Kagal

Tim Berners-Lee

Research Areas

Impact Areas

Lead

Lalana Kagal

Tim Berners-Lee

Lalana Kagal

Tim Berners-Lee

Research Group

Distributed Robotics Laboratory

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

+13

Daniela Rus

Leads

Daniela Rus

Research Areas

Impact Areas

Lead

Daniela Rus

+13

Daniela Rus

Research Group

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

Imagination, Computation, and Expression Laboratory (ICE Lab)

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

Peter Mawhorter

D. Fox Harrell

Leads

D. Fox Harrell

Research Areas

Impact Areas

Manufacturing

Lead

D. Fox Harrell

Peter Mawhorter

D. Fox Harrell

Research Group

Infolab

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

Boris Katz

Leads

Boris Katz

Research Areas

Impact Areas

Lead

Boris Katz

Research 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

Machine Learning

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

Leads

Tamara Broderick

Tommi Jaakkola

Stefanie Jegelka

Leslie Kaelbling

David Sontag

Research Areas

Impact Areas

Lead

Tamara Broderick

Tommi Jaakkola

Stefanie Jegelka

Leslie Kaelbling

David Sontag

Research Group

Sensing, Learning and Inference

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

John Fisher

Leads

John Fisher

Research Areas

Impact Areas

Internet of Things

Lead

John Fisher

Research Group

Spoken Language Systems Group

Our goal is to create technology that makes it possible for everyone in the world to interact with with computers via natural spoken language.

Jim Glass

Leads

Jim Glass

Research Areas

Impact Areas

Lead

Jim Glass

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

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

Vision Group

Our researchers create state-of-the-art systems to better recognize objects, people, scenes, behaviors and more, with applications in health-care, gaming, tagging systems and more.

Leads

Ted Adelson

Fredo Durand

John Fisher

William Freeman

Polina Golland

Eric Grimson

Berthold Horn

Aude Oliva

Antonio Torralba

Research Areas

Impact Areas

Lead

Ted Adelson

Fredo Durand

John Fisher

William Freeman

Polina Golland

Eric Grimson

Berthold Horn

Aude Oliva

Antonio Torralba

Community of Research

Visual Computing Community of Research

The shared mission of Visual Computing is to connect images and computation, spanning topics such as image and video generation and analysis, photography, human perception, touch, applied geometry, and more.

+10

William Freeman

Leads

William Freeman

Research Areas

Impact Areas

Learning and Intelligent Systems

Lead

William Freeman

+10

William Freeman

30 Project Results

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

Automatic Speech Recognition

Automatic speech recognition (ASR) has been a grand challenge machine learning problem for decades. Our ongoing research in this area examines the use of deep learning models for distant and noisy recording conditions, multilingual, and low-resource scenarios.

Sameer Khurana

Jim Glass

Leads

Sameer Khurana

Jim Glass

Research Areas

Impact Areas

Sameer Khurana

Jim Glass

Project

Autonomous Vehicle Databases

Data Systems Group

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

Michael Stonebraker

Sam Madden

Leads

Michael Stonebraker

Sam Madden

Research Areas

Impact Areas

Michael Stonebraker

Sam Madden

Project

Bayesian Optimization for Global Optimization of Expensive Black-box Functions

Learning and Intelligent Systems

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

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

Computation Structures Group

Project

BlueDBM: Distributed Flash Storage for Big Data Analytics

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

Leads

Research Areas

Impact Areas

Cognitive AI Community of Research

Project

CliNER: Clinical Concept Extraction

Clinical concept extraction (CCE) of named entities - such as problems, tests, and treatments - aids in forming an understanding of notes and provides a foundation for many downstream clinical decision-making tasks. Historically, this task has been posed as a standard named entity recognition (NER) sequence tagging problem, and solved with feature-based methods using hand-engineered domain knowledge. Recent advances, however, have demonstrated the efficacy of LSTM-based models for NER tasks, including CCE. This work presents CliNER 2.0, a simple-to-install, open-source tool for extracting concepts from clinical text. CliNER 2.0 uses a word- and character- level LSTM model, and achieves state-of-the-art performance. For ease of use, the tool also includes pre-trained models available for public use.

Leads

William Boag

Elena Sergeeva

Peter Szolovits

Anna Rumshisky

Research Areas

Impact Areas

Project

Community Question Answering

Our main goal is to automatically search for relevant answers among many responses provided for a given question (Answer Selection), and search for relevant questions to reuse their existing answers (Question Retrieval).

Mitra Mohtarami

Leads

Mitra Mohtarami

Research Areas

Impact Areas

Mitra Mohtarami

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

Crossing the Vision-Language Boundary

Building models that learn spoken language by seeing and hearing

Leads

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

Drones that Drive

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

Leads

Research Areas

Impact Areas

Project

EQ-Radio: Emotion Recognition using Wireless Signals

Networks at MIT

EQ-Radio can infer a person’s emotions using wireless signals. It transmits an RF signal and analyzes its reflections off a person’s body to recognize his emotional state (happy, sad, etc.).

Dina Katabi

Leads

Dina Katabi

Research Areas

Impact Areas

Internet of Things

Dina Katabi

Project

Fact-Checking and Reasoning

Our main goal is to develop fact checking algorithms that can assess the credibility of claims mentioned in the textual statements and provide interpretable valid evidence that explains why a certain claim is considered as factually true or fake.

Mitra Mohtarami

Jim Glass

Leads

Mitra Mohtarami

Jim Glass

Research Areas

Impact Areas

Geometric Data Processing Group

Mitra Mohtarami

Jim Glass

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

Justin Solomon

Project

Geometry in Large-Scale 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

Anyscale Learning for All ALFA

Internet of Things

Justin Solomon

Stefanie Jegelka

Project

GIGABEATS: Data science for medical sensor data

Our goal is to help medical researchers and clincians understand the growing repositories of waveform and signal data collected from critically ill patients.

Una-May O'Reilly

Leads

Una-May O'Reilly

Research Areas

Impact Areas

Una-May O'Reilly

Project

Jenga: Using chip memory more efficiently

Our system for generating ad hoc “cache hierarchies” increases processing speed while reducing energy consumption

Leads

Research Areas

Impact Areas

Project

Low-Power Speech Processing Circuits

The creation of low-power circuits capable of speech recognition and speaker verification will enable spoken interaction on a wide variety of devices in the era of Internet of Things.

Leads

Research Areas

Anyscale Learning for All ALFA

Impact Areas

Project

MOOC Learner Project: Data science for e-learning

The MOOC Learner Project provides learning scientists, instructional designers and online education specialists with open source software that enables them to efficiently extract teaching and learning insights from the data collected when students learn on the edX or open edX platform.

Una-May O'Reilly

Erik Hemberg

Leads

Una-May O'Reilly

Erik Hemberg

Research Areas

Impact Areas

Geometric Data Processing Group

Una-May O'Reilly

Erik Hemberg

Project

Optimal transport for statistics and machine learning

Linking probability with geometry to improve the theory and practice of machine learning

Justin Solomon

Leads

Justin Solomon

Research Areas

Impact Areas

Decentralized Information Group

Justin Solomon

Project

PrivacyML - A Privacy Preserving Framework for Machine Learning

Cognitive AI Community of Research

Computing & Society Community of Research

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

Geometric Data Processing Group

Impact Areas

Lalana Kagal

Vaikkunth Mugunthan

Project

Sensible Deep Learning for 3D Data

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

Justin Solomon

Leads

Justin Solomon

Research Areas

Impact Areas

Manufacturing

Justin Solomon

Project

SoFi - The Soft Robotic Fish

Exploration of underwater life with an acoustically controlled soft robotic fish

Joseph DelPreto

Leads

Joseph DelPreto

Research Areas

Impact Areas

Simit: A Language for Computing on Sparse Systems

Joseph DelPreto

59 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

Robust Learning for Autonomous Vehicles

Compilers, architectures, software engineering

Alexander Amini

Graduate Student

PhD Candidate. Deep Learning; Robotics

E Amini@mit.edu

Lead

Member

Self-Driving Vehicles

Natural Language Processing Group

PhD Candidate. Deep Learning; Robotics

Brandon Araki

Graduate Student

E araki@csail.mit.edu

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

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

Tim Berners-Lee

Professor

Systems, privacy, inventor of the World Wide Web

E timbl@w3.org

T 253-5702

Lead

Decentralized Information Group

World Wide Web Consortium

Solid: Social Linked Data

Member

Computing & Society Community of Research

Systems, privacy, inventor of the World Wide Web

Laurent Bindschaedler

Postdoctoral Fellow

Systems for Big Data and ML. ML for Systems.

E bindscha@mit.edu

Member

Data Systems Group

Systems for Big Data and ML. ML for Systems.

PI
Core/Dual

Tamara Broderick

Associate Professor

Machine learning, statistics, Bayesian methods, inference

E tbroderick@csail.mit.edu

T 324-6749

Lead

Scalable Bayesian Inference via Adaptive Data Summaries

Scalable Bayesian inference with optimization

Broderick Lab

Member

Clinical Machine Learning Group

Machine learning, statistics, Bayesian methods, inference

Irene Chen

Graduate Student

Machine learning, healthcare, fairness

E iychen@mit.edu

Member

Unsupervised Speech Processing

Machine learning, healthcare, fairness

Xuhao Chen

Postdoctoral Associate

Parallel Computer Architecture, Data Mining, Machine Learning

E cxh@mit.edu

Parallel Computer Architecture, Data Mining, Machine Learning

Yu-An Chung

Graduate Student

Speech and language processing, machine learning

E andyyuan@mit.edu

Lead

Member

Is the Casino using a Riffle Shuffle?

Speech and language processing, machine learning

PI
Core/Dual

Costis Daskalakis

Associate Professor

Algorithms, Economics, Game Theory, Statistics, Machine Learning

E costis@csail.mit.edu

T 253-9643

Lead

Algorithms Group

Understanding Convergence of Iterative Algorithms

Theory of Computation Community of Research

Member

Center for Deployable Machine Learning (CDML)

Algorithms, Economics, Game Theory, Statistics, Machine Learning

Azim Dehghani Amirabad

Postdoctoral Associate

Machine learning, Bioinformatics

E azimd@csail.mit.edu

Machine learning, Bioinformatics

PI
Core/Dual

Fredo Durand

Professor

Vision, graphics, computational photography

E fredo@csail.mit.edu

T 253-7223

Lead

Computer Graphics Group

Computational Understanding of Visualizations and Graphic Designs

Vision Group

Member

Computational Bounce Flash for Indoor Portraits

Halide

Visual Computing Community of Research

Vision, graphics, computational photography

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

Barış Ekim

Graduate Student

E ekim@csail.mit.edu

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.

Wei Fang

Graduate Student

Language and speech processing, machine learning

E weifang@mit.edu

Member

Sensing, Learning and Inference

Language and speech processing, machine learning

Sue Felshin

Research Scientist

E sfelshin@csail.mit.edu

T 253-2965

Lead

START System

Member

Infolab

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

PI
Core/Dual

William Freeman

Professor

Vision, machine learning, Bayesian modeling

E billf@csail.mit.edu

T 253-8828

Lead

Vision Group

Computer Graphics Group

Visual Computing Community of Research

Member

Single-Image 3D Interpreter Network

Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks

Learning the Arrow of Time from Videos

3D Generative Adversarial Networks

Embodied Intelligence Community of Research

Vision, machine learning, Bayesian modeling

PI
Core/Dual

Jim Glass

Senior Research Scientist

speech and language processing

E glass@mit.edu

T 253-1640

Lead