Research

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

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 Group

Clinical Decision-Making Group

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

+11

Peter Szolovits

Leads

Peter Szolovits

Research Areas

Impact Areas

Lead

Peter Szolovits

+11

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

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.

+12

Daniela Rus

Leads

Daniela Rus

Research Areas

Impact Areas

Lead

Daniela Rus

+12

Daniela Rus

Research Group

Genesis Group

The Genesis Group focuses on developing an account of human intelligence with special
emphasis on developing computational models of how people tell, perceive and understand
stories.

Leads

Research Areas

Impact Areas

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

Community of Research

Human-Computer Interaction Community of Research

The focus of the HCI CoR is inventing new systems and technology that lie at the interface between people and computation, and understanding their design, implementation, and societal impact.

Stefanie Mueller

Leads

Stefanie Mueller

Research Areas

Impact Areas

Lead

Stefanie Mueller

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

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 Group

Learning and Intelligent Systems

We conduct interdisciplinary research aimed at discovering the principles underlying the design of artificially intelligent robots.

Leslie Kaelbling

Tomas Lozano-Perez

Leads

Leslie Kaelbling

Tomas Lozano-Perez

Research Areas

Impact Areas

Transportation

Lead

Leslie Kaelbling

Tomas Lozano-Perez

Leslie Kaelbling

Tomas Lozano-Perez

Research Group

Lecturers

Lecturers in CSAIL

Leads

Research Areas

Impact Areas

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

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

Internet of Things

Lead

Hal Abelson

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

39 Project Results

Project

3D Generative Adversarial Networks

We study the problem of 3D object generation. We propose a novel framework, 3D Generative Adversarial Network (3D-GAN), leveraging recent advances in volumetric convolutional networks and generative adversarial nets.

Leads

Research Areas

Impact Areas

Learning and Intelligent Systems

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

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

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

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

Decentralized Information Group

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

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

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

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.

Marzyeh Ghassemi

John Guttag

Leads

Marzyeh Ghassemi

John Guttag

Research Areas

Impact Areas

Marzyeh Ghassemi

John Guttag

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

Distributed Robotics Laboratory

Neil Thompson

Charles E. Leiserson

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

Vertical AI Community of Research

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

Geometric Data Processing Group

Internet of Things

Dina Katabi

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

Anyscale Learning for All ALFA

Justin Solomon

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

Health-related Biomarkers from Speech

From audio recordings of clinician-subject interactions, we determine the spoken language bio-markers that are associated with health outcomes, such as dementia and depression.

Leads

Research Areas

Impact Areas

Project

Information Retrieval for Cancer Treatments in Clinical Literature and Trial Eligibility

A "precision medicine" approach for finding relevant cancer treatments in clinical literature and eligible trials. For a given patient with associated demographics (age, gender) and disease (cancer type, genetic variants), we query a database of all pubmed articles and clinicaltrials.gov trials using NLP techniques to find the most useful and relevant treatments for the patient. Our ensemble-based system performed very well in the TREC 2016 Precision Medicine challenge.

Peter Szolovits

William Boag

Leads

Peter Szolovits

William Boag

Research Areas

Impact Areas

Peter Szolovits

William Boag

Project

Monitoring Fetal Health

We develop algorithms for fetal MRI interpretation, to enable noninvasive fetal monitoring from MRI.

Polina Golland

Leads

Polina Golland

Research Areas

Impact Areas

Anyscale Learning for All ALFA

Polina Golland

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

Una-May O'Reilly

Erik Hemberg

Project

Multivariate Signal Representations That Predict ICU Interventions

Our focus is using computational tools to summarize health-related data to help clinicians focus on decision-making rather than just keeping up with the data.

Peter Szolovits

Leads

Peter Szolovits

Research Areas

Impact Areas

Data-Driven Inference Group

Peter Szolovits

Project

Predicting Adverse Events Across Changing Electronic Health Record Systems

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

John Guttag

Peter Szolovits

Leads

John Guttag

Peter Szolovits

Research Areas

Impact Areas

John Guttag

Peter Szolovits

58 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

Visual Computing Community of Research

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

PI
Core/Dual

Regina Barzilay

Professor

Natural language processing, machine learning

E regina@csail.mit.edu

T 258-5706

Lead

Natural Language Processing Group

Aspect-Augmented Adversarial Networks for Domain Adaptation

Member

Vertical AI Community of Research

Synthetically-Identified Clinical Notes

Natural language processing, machine learning

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

Model-Based Embedded and Robotics Systems Group

Clinical NLP

Richard Camilli

Research Affiliate

E romeo@mit.edu

Member

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

Speech and language processing, machine learning

Adrian Dalca

Research Scientist

E adalca@csail.mit.edu

Member

Clinical Neuroimaging

Mustafa Doga Dogan

Graduate Student

E doga@mit.edu

Member

HCI Engineering Group

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

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.

Sue Felshin

Research Scientist

E sfelshin@csail.mit.edu

T 253-2965

Lead

START System

Member

Infolab

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

Quantification of Pulmonary Edema in Chest Radiographs

Monitoring Fetal Health

Cardiac MRI analysis

Clinical Neuroimaging

Member

Visual Computing Community of Research

Vision, medical imaging, statistical inference

PI
Core/Dual

John Guttag

Professor

Machine learning, medicine, data-driven inference

E guttag@csail.mit.edu

T 253-6022

Lead

Data-Driven Inference Group

Hidden Influencers, Risk and Causes of Infection

Predicting Adverse Events Across Changing Electronic Health Record Systems

Machine Learning for Insights in Basketball Strategy

Detecting Voice Misuse to Diagnose Disorders

Member

Systems Community of Research

Machine learning, medicine, data-driven inference

Lelia Hampton

Graduate Student

Ph.D. Student

E lelia@mit.edu

Ph.D. Student

Ramin Hasani

Postdoctoral Associate

Machine learning Scientist

E rhasani@csail.mit.edu

Machine learning Scientist

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

Systems Community of Research

Wildcard

Software design, programming, systems

PI
Core/Dual

Leslie Kaelbling

Professor

Robotics, machine learning, motion planning

E lpk@csail.mit.edu

T 258-9695

Lead

Learning and Intelligent Systems

Learning and Optimization

Robotic Planning and Manipulation with Force Information

Reliable Robotic Construction of Multi-object Arrangements

Learning and Planning with Compressed Linear Expectation Models

Active Learning of Models for Planning

Task and Motion Planning for Autonomous Robots

Robust Intelligent Robots

Member

Robust Intelligent Robots

Embodied Intelligence Community of Research

Robotics, machine learning, motion planning

PI
Core/Dual

Lalana Kagal

Principal Research Scientist

Privacy, web decentralization, distributed data

E lkagal@csail.mit.edu

T 253-5845

Lead

Decentralized Information Group

The Car Can Explain!

Internet Policy Research Initiative

Solid: Social Linked Data

PrivacyML - A Privacy Preserving Framework for Machine Learning

Member

Computing & Society Community of Research