Research

Impact Areas

Lead

Una-May O'Reilly

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

Decentralized Information Group

Impact Areas

Lead

Martin Rinard

1 Project Results matching all criteria

Project

PrivacyML - A Privacy Preserving Framework for Machine Learning

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

Anyscale Learning for All ALFA

Impact Areas

Lalana Kagal

Vaikkunth Mugunthan

2 People Results matching all criteria

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

Adversarial Cyber Security

GIGABEATS: Data science for medical sensor data

MOOC Learner Project: Data science for e-learning

Member

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

27 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

Community of Research

Applied Machine Learning Community of Research

This CoR brings together researchers at CSAIL working across a broad swath of application domains. Within these lie novel and challenging machine learning problems serving science, social science and computer science.

Una-May O'Reilly

Leads

Una-May O'Reilly

Research Areas

Impact Areas

Lead

Una-May O'Reilly

Research Group

Broderick Lab

We work in the areas of statistics and machine learning.

Tamara Broderick

Leads

Tamara Broderick

Research Areas

Impact Areas

Lead

Tamara Broderick

Research Group

Center for Brains, Minds and Machines

Our main goal is developing a computationally based understanding of human intelligence and establishing an engineering practice based on that understanding.

Tomaso Poggio

Leads

Tomaso Poggio

Research Areas

Impact Areas

Lead

Tomaso Poggio

Research Center

Center for Deployable Machine Learning (CDML)

The MIT Center for Deployable Machine Learning (CDML) works towards creating AI systems that are robust, reliable and safe for real-world deployment.

Aleksander Madry

Leads

Aleksander Madry

Research Areas

Impact Areas

Lead

Aleksander Madry

Research Group

Clinical Decision-Making Group

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

+10

Peter Szolovits

Leads

Peter Szolovits

Research Areas

Impact Areas

Manufacturing

Lead

Peter Szolovits

+10

Peter Szolovits

Research Group

Clinical Machine Learning Group

Our group is interested in using machine learning and artificial intelligence to transform health care.

David Sontag

Leads

David Sontag

Research Areas

Impact Areas

Lead

David Sontag

Research Group

Computational Cognitive Science Group

We study the computational basis of human learning and inference.

Joshua Tenenbaum

Leads

Joshua Tenenbaum

Research Areas

Impact Areas

Lead

Joshua Tenenbaum

Research Group

Computational Genomics Group

We develop new machine learning techniques and algorithms to model the transcriptional regulatory networks that control gene expression programs in living cells.

Dave Gifford

Leads

Dave Gifford

Research Areas

Impact Areas

Lead

Dave Gifford

Research Group

Computational Perception & Cognition

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

Aude Oliva

Leads

Aude Oliva

Research Areas

Impact Areas

Lead

Aude Oliva

Community of Research

Computing & Society Community of Research

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

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

Medical Vision Group

We develop new algorithms for medical image analysis and visualization of medical imagery.

Polina Golland

Leads

Polina Golland

Research Areas

Impact Areas

Lead

Polina Golland

Research Group

Natural Language Processing Group

Our research encompasses all aspects of NLP, from modeling basic linguistic phenomena to designing practical text processing systems, and developing new machine learning methods.

Regina Barzilay

Tommi Jaakkola

Leads

Regina Barzilay

Tommi Jaakkola

Research Areas

Impact Areas

Lead

Regina Barzilay

Tommi Jaakkola

Regina Barzilay

Tommi Jaakkola

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

Energy

Internet of Things

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

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

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

Computer Architecture

Learning and Intelligent Systems

Impact Areas

Lead

Sam Madden

+21

Sam Madden

43 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

Human-Computer Interaction Community of Research

Entertainment

Leslie Kaelbling

Tomas Lozano-Perez

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

Interactive Robotics Group

Impact Areas

Daniel Jackson

Project

Apprenticeship Scheduling: Learning to Schedule From Human Experts

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

Leads

Research Areas

Impact Areas

Weiss Laboratory for Synthetic Biology

Manufacturing

Project

Artificial tissue homeostasis

In order to be able to design synthetic organs that function autonomously, we will need to engineer artificial tissue homeostasis. To control the size of these artificial tissues, two major mechanisms will have to be engineered.

Leads

Research Areas

Impact Areas

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

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

Transportation

Michael Stonebraker

Sam Madden

Project

AWE-CM Vectors: Augmenting Word Embeddings with a Clinical Metathesaurus

Adding domain knowledge to word embeddings.

Peter Szolovits

Leads

Peter Szolovits

Research Areas

Impact Areas

Peter Szolovits

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

Decentralized Information Group

Energy

Transportation

Project

The Car Can Explain!

Computing & Society Community of Research

Developing techniques to allow self-driving cars and other AI-driven systems to explain behaviors and failures.

Gerald Sussman

Lalana Kagal

Leads

Gerald Sussman

Lalana Kagal

Research Areas

Impact Areas

Transportation

Gerald Sussman

Lalana Kagal

Project

Cardiac MRI analysis

Medical Vision Group

We develop image analysis algorithms for whole-heart cardiac MRI in patients with severe congenital heart disease.

Polina Golland

Leads

Polina Golland

Research Areas

Impact Areas

Polina Golland

Project

Clinical Intervention Prediction with Neural Networks

Integrating multi-modal clinical data and using recurrent and convolution neural networks to predict when patients will need important interventions.

Leads

Research Areas

Impact Areas

Project

Clinical Neuroimaging

Medical Vision Group

We develop novel algorithms for neuroimage segmentation, registration, and joint modeling of brain structure with clinical and genetic data.

Polina Golland

Leads

Polina Golland

Research Areas

Impact Areas

Polina Golland

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

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

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

Detecting Voice Misuse to Diagnose Disorders

Our team uses accelerometers and machine learning to help detect vocal disorders. We capture data about the motions of patient's vocal folds to determine if their vocal behavior is normal or abnormal.

John Guttag

Leads

John Guttag

Research Areas

Impact Areas

John Guttag

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

Vertical AI Community of Research

Stefanie Jegelka

Suvrit Sra

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

Entertainment

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

Internet of Things

Justin Solomon

Stefanie Jegelka

70 People Results

PI
Core/Dual

Ted Adelson

Professor

Vision, touch sensing, robotics

E adelson@csail.mit.edu

T 253-0645

Lead

Embodied Intelligence Community of Research

Blood Pressure Imager

Member

Robust Learning for Autonomous Vehicles

Vision, touch sensing, robotics

Monica Agrawal

Graduate Student

E magrawal@mit.edu

Leandro Agudelo

Research Scientist

Systems Genomics, CompBio, Topological Integrative Biology, Biology

E lagudelo@csail.mit.edu

Systems Genomics, CompBio, Topological Integrative Biology, Biology

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

Vertical AI Community of Research

Natural language processing, machine learning

Cenk Baykal

Graduate Student

E baykal@mit.edu

RM 32-376C

Member

Coresets for Machine Learning Algorithms

Laurent Bindschaedler

Postdoctoral Fellow

Systems for Big Data and ML. ML for Systems.

E bindscha@mit.edu

Member

Synthetically-Identified Clinical Notes

Systems for Big Data and ML. ML for Systems.

William Boag

Graduate Student

Clinical NLP

E wboag@mit.edu

Lead

Information Retrieval for Cancer Treatments in Clinical Literature and Trial Eligibility

CliNER: Clinical Concept Extraction

Quantifying Racial Disparities in End-of-Life Care

Member

Clinical NLP

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

Vertical AI Community of Research

Machine learning, statistics, Bayesian methods, inference

Geeticka Chauhan

Graduate Student

E geeticka@mit.edu

Member

Quantification of Pulmonary Edema in Chest Radiographs

Irene Chen

Graduate Student

Machine learning, healthcare, fairness

E iychen@mit.edu

Member

Clinical Machine Learning Group

Unsupervised Speech Processing

Machine learning, healthcare, fairness

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

Member

Computational Bounce Flash for Indoor Portraits

Halide

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

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

Sensing, Learning and Inference

Member

Vision, machine learning, signal processing

PI
Core/Dual

Jim Glass

Senior Research Scientist

speech and language processing

E glass@mit.edu

T 253-1640

Lead

Designing Information-Rich Embedding Spaces

Unsupervised Learning of Interpretable Representations from Sequential Data

Fact-Checking and Reasoning

Speaker Verification and Diarization

Automatic Speech Recognition

Language and Dialect Identification

Member

Using Computers to Eat Healthier

Low-Power Speech Processing Circuits

Crossing the Vision-Language Boundary

Unsupervised Speech Processing

Arabic Language Processing

Health-related Biomarkers from Speech

Community Question Answering

Understanding Language Representations in Deep Learning Models

Embodied Intelligence Community of Research

speech and language processing

PI
Core/Dual

Polina Golland

Professor

Vision, medical imaging, statistical inference

E polina@csail.mit.edu

T 253-8005

Lead

Medical Vision Group

Quantification of Pulmonary Edema in Chest Radiographs

Monitoring Fetal Health

Cardiac MRI analysis

Clinical Neuroimaging

Member