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

Programming Languages & Software Engineering

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.

+10

Peter Szolovits

Leads

Peter Szolovits

Research Areas

Impact Areas

Lead

Peter Szolovits

+10

Peter Szolovits

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

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.

+11

Daniela Rus

Leads

Daniela Rus

Research Areas

Impact Areas

Lead

Daniela Rus

+11

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

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

Entertainment

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

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

Sussman Lab

We focus on understanding the problem-solving strategies used by scientists and engineers, with the goals of automating parts of the process and formalizing educational methods.

Gerald Sussman

Leads

Gerald Sussman

Research Areas

Programming Languages & Software Engineering

Impact Areas

Lead

Gerald Sussman

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

Programming Languages & Software Engineering

Impact Areas

Lead

Martin Rinard

Research Group

Weiss Laboratory for Synthetic Biology

The Weiss Lab seeks to create integrated biological systems capable of autonomously performing useful tasks, and to elucidate the design principles underlying complex phenotypes.

Leads

Research Areas

Impact Areas

14 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

Machine Learning

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

Interactive Robotics Group

Entertainment

Leslie Kaelbling

Tomas Lozano-Perez

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

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

Learning and Intelligent Systems

Impact Areas

Sameer Khurana

Jim Glass

Project

Bayesian Optimization for Global Optimization of Expensive Black-box Functions

Machine Learning

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

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

Anyscale Learning for All ALFA

Impact Areas

Wireless

Hanshen Xiao

Project

MOOC Learner Project: Data science for e-learning

Applied Machine Learning Community of Research

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

Privacy-Preserving Decentralized Optimization

To enable privacy preservation in decentralized optimization, differential privacy is the most commonly used approach. However, under such scenario, the trade-off between accuracy (even efficiency) and privacy is inevitable. In this project, distributed numerical optimization scheme incorporated with lightweight cryptographic information sharing are explored. The affect on the convergence rate from network topology is considered.

Hanshen Xiao

Leads

Hanshen Xiao

Research Areas

Impact Areas

Decentralized Information Group

Wireless

Hanshen Xiao

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

Geometric Data Processing Group

Impact Areas

Lalana Kagal

Vaikkunth Mugunthan

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

Justin Solomon

Project

Single-Image 3D Interpreter Network

We aim to understand 3D object structure from a single image. We propose an end-to-end framework which sequentially estimates 2D keypoint heatmaps and 3D object structure, by training it on both real 2D-annotated images and synthetic 3D data and by integrating a 3D-to-2D projection layer.

Leads

Research Areas

Impact Areas

Imagination, Computation, and Expression Laboratory (ICE Lab)

Project

Toward Using Virtual Identities in Computer Science Learning for Broadening Participation

Our research seeks to discover best practices for using avatars to enhance performance, engagement, and STEM identity development for diverse public middle and high school computer science students. As sites of our research we run workshops in which students learn computer science in fun, relevant ways, and develop self-images as computer scientists.

Sneha Veeragoudar Harrell

Aziria Rodriguez

D. Fox Harrell

Leads

D. Fox Harrell

Research Areas

Impact Areas

Entertainment

Sneha Veeragoudar Harrell

Aziria Rodriguez

D. Fox Harrell

Project

Unsupervised Speech Processing

All humans process vast quantities of unannotated speech and manage to learn phonetic inventories, word boundaries, etc., and can use these abilities to acquire new word. Why can't ASR technology have similar capabilities? Our goal in this research project is to build speech technology using unannotated speech corpora.

Yu-An Chung

Sameer Khurana

Leads

Yu-An Chung

Sameer Khurana

Research Areas

Impact Areas

Yu-An Chung

Sameer Khurana

Project

Who Knows What? Perspective-Enabled Story Understanding

Genesis Group

To understand human intelligence, we must be able to model how humans understand stories from multiple characters' perspectives.

Leads

Research Areas

Impact Areas

32 People Results

PI
Core/Dual

Ted Adelson

Professor

Vision, touch sensing, robotics

E adelson@csail.mit.edu

T 253-0645

Lead

Blood Pressure Imager

Visual Computing Community of Research

Member

Vision, touch sensing, robotics

Noam Buckman

Graduate Student

PhD Candidate. Autonomous vehicles. Multi-robot systems.

E nbuckman@mit.edu

Member

Distributed Robotics Laboratory

Self-Driving Vehicles

PhD Candidate. Autonomous vehicles. Multi-robot systems.

Richard Camilli

Research Affiliate

E romeo@mit.edu

Member

Model-Based Embedded and Robotics Systems Group

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

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

speech and language processing

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

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

Algorithms Group

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

Theory of Computation Community of Research

Systems Community of Research

Helping people manage information

Alexandre Kaspar

Graduate Student

Graphics, crowdsourcing and hybrid fabrication.

E akaspar@mit.edu

Lead

Crowdsourcing in Graphics and Vision

Computational Knitting: Patterning and Shaping for Everyone

Graphics, crowdsourcing and hybrid fabrication.

PI
Core/Dual

Dina Katabi

Professor

Wireless, networks, machine learning

E dina@csail.mit.edu

T 324-6027

Lead

Networks at MIT

EQ-Radio: Emotion Recognition using Wireless Signals

Member

Vertical AI Community of Research

Wireless, networks, machine learning

PI
Core/Dual

Boris Katz

Principal Research Scientist

Natural language processing

E boris@csail.mit.edu

T 253-6032

Lead

Infolab

START System

Semantic Parsing using Vision

Generating Plans for Agents using Video and Language

Inferring “Theory of Mind” with vision and language

Artificial Social Intelligence for Successful Teams (ASIST)

Member

Center for Brains, Minds and Machines

Clinical Decision-Making Group

Natural language processing

Fern Keniston

Senior Administrative Assistant

Research and Education Support

E fern@csail.mit.edu

T 253-5860

RM 32/ 32-250A/ 391

Member

Research and Education Support

Sameer Khurana

Graduate Student

unsupervised speech processing, automatic speech recognition

E skhurana@mit.edu

Lead

Automatic Speech Recognition

Unsupervised Speech Processing

Language and Dialect Identification

Member

Learning and Intelligent Systems

unsupervised speech processing, automatic speech recognition

Kimberle Koile

Lecturer

E kkoile@csail.mit.edu

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.

PI
Core/Dual

Tomas Lozano-Perez

Professor

Robotics, artificial intelligence

E tlp@csail.mit.edu

T 253-7889

Lead

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

Anyscale Learning for All ALFA

Robotics, artificial intelligence

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

Applied Machine Learning Community of Research

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

Helping robots learn using demonstrations

CSAIL director, robotics, AI, data science, privacy

PI
Core/Dual

Julie Shah

Associate Professor

Robotics, machine learning, artificial intelligence

E julie_a_shah@csail.mit.edu

T 324-4879

Lead

Interactive Robotics Group

Robots that collaborate with humans to form team plans

Robots that Quickly Adjust Team Plans to Disturbance

Human-Guided Transfer for Robot Learning

Efficient Communication for Human-Machine Teams

Member

Apprenticeship Scheduling: Learning to Schedule From Human Experts