Research

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.

+14

Peter Szolovits

Leads

Peter Szolovits

Research Areas

Impact Areas

Lead

Peter Szolovits

+14

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

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

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.

Patrick Winston

Leads

Patrick Winston

Research Areas

Impact Areas

Lead

Patrick Winston

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.

+10

Leslie Kaelbling

Tomas Lozano-Perez

Leads

Leslie Kaelbling

Tomas Lozano-Perez

Research Areas

Impact Areas

Lead

Leslie Kaelbling

Tomas Lozano-Perez

Leslie Kaelbling

Tomas Lozano-Perez

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

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

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

Impact Areas

Lead

Gerald Sussman

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

Ruth Rosenholtz

Antonio Torralba

Research Areas

Impact Areas

Lead

Ted Adelson

Fredo Durand

John Fisher

William Freeman

Polina Golland

Eric Grimson

Berthold Horn

Aude Oliva

Ruth Rosenholtz

Antonio Torralba

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

Sensing, Learning and Inference

We focus on the analysis of complex, high-dimensional data.

John Fisher

Leads

John Fisher

Research Areas

Impact Areas

Internet of Things

Lead

John Fisher

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

Debayan Gupta

Leads

Debayan Gupta

Research Areas

Impact Areas

Lead

Debayan Gupta

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

Medical Vision Group

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

+10

Polina Golland

Leads

Polina Golland

Research Areas

Impact Areas

Lead

Polina Golland

Polina Golland

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.

+17

Daniela Rus

Leads

Daniela Rus

Research Areas

Impact Areas

Lead

Daniela Rus

+17

Daniela Rus

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.

+21

Jim Glass

Leads

Jim Glass

Research Areas

Impact Areas

Lead

Jim Glass

+21

Jim Glass

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

Natural Language Processing Group

Impact Areas

Lead

Una-May O'Reilly

62 Project Results matching all criteria

Project

Aspect-Augmented Adversarial Networks for Domain Adaptation

We propose a novel aspect-augmented adversarial network for cross-aspect and cross-domain adaptation tasks. The effectiveness of our approach suggests the potential application of adversarial networks to a broader range of NLP tasks for improved representation learning, such as machine translation and language generation.

Regina Barzilay

Tommi Jaakkola

Leads

Regina Barzilay

Tommi Jaakkola

Research Areas

Regina Barzilay

Tommi Jaakkola

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.

Jiajun Wu

Leads

Jiajun Wu

Research Areas

Impact Areas

Jiajun Wu

Project

Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks

In our work we developed a model that is able to synthesize many probable future frames with just a single image as input.

Jiajun Wu

Leads

Jiajun Wu

Research Areas

Jiajun Wu

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.

Jiajun Wu

Leads

Jiajun Wu

Research Areas

Impact Areas

Jiajun Wu

Project

Learning Strategic Games

Our goal is to develop new tools for modeling diverse multi-agent settings, and design estimation algorithms to unravel the strategic interactions among the agents.

Vikas Garg

Tommi Jaakkola

Leads

Vikas Garg

Tommi Jaakkola

Research Areas

Vikas Garg

Tommi Jaakkola

Project

Bayesian Optimization for Global Optimization of Expensive Black-box Functions

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.

Zi Wang

Stefanie Jegelka

Leads

Zi Wang

Stefanie Jegelka

Research Areas

Learning and Intelligent Systems

Zi Wang

Stefanie Jegelka

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.

Leads

Zi Wang

Leslie Kaelbling

Tomas Lozano-Perez

Research Areas

Impact Areas

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.

Patrick Winston

Leads

Patrick Winston

Research Areas

Impact Areas

Data-Driven Inference Group

Patrick Winston

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.

Leads

Jen Gong

Tristan Naumann

John Guttag

Peter Szolovits

Research Areas

Impact Areas

Project

Understanding Language Representations in Deep Learning Models

Our goal is to explore language representations in computational models. We develop new models for representing natural language and investigate how existing models learn language, focusing on neural network models in key tasks like machine translation and speech recognition.

Yonatan Belinkov

Leads

Yonatan Belinkov

Research Areas

Imagination, Computation, and Expression Laboratory (ICE Lab)

Yonatan Belinkov

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

Sneha Veeragoudar Harrell

Aziria Rodriguez

D. Fox Harrell

Project

Autonomous Vehicle Databases

Database 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

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

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

Peter Szolovits

Project

Clinical Note Representations That Predict ICU Mortality/Re-Admission

Our focus is on improving health-related outcomes by creating machine learning models that improve human risks.

Peter Szolovits

Leads

Peter Szolovits

Research Areas

Impact Areas

Weiss Laboratory for Synthetic Biology

Peter Szolovits

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

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

Adversarial Cyber Security

Our goal is to understand the nature of cyber security arms races between malicious and bonafide parties. Our vision is autonomous cyber defenses that anticipate and take measures against counter attacks.

Una-May O'Reilly

Leads

Una-May O'Reilly

Research Areas

Impact Areas

Una-May O'Reilly

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

Distributed Robotics Laboratory

Una-May O'Reilly

Project

Drones that Drive

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

Brandon Araki

Leads

Brandon Araki

Research Areas

Impact Areas

Interactive Robotics Group

Brandon Araki

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

Distributed Robotics Laboratory

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

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.

Leads

Chengtao Li

Stefanie Jegelka

Suvrit Sra

Research Areas

Impact Areas

Project

Towards Adversarially Robust Deep Neural Networks

We work towards a principled understanding of the non-robust nature of deep learning classifiers and build approaches to training reliably robust classifiers.

Aleksander Madry

Leads

Aleksander Madry

Research Areas

Impact Areas

Aleksander Madry

4 People Results matching all criteria

Francois Grondin

Postdoctoral Fellow

Postdoctoral Research Associate

E fgrondin@csail.mit.edu

Member

Fact-Checking and Reasoning

Postdoctoral Research Associate

Mitra Mohtarami

Research Scientist

E mitra@csail.mit.edu

Lead

Community Question Answering

Arabic Language Processing

Member

Tae-Hyun Oh

Postdoctoral Associate

E taehyun@mit.edu

Markus Ryll

Postdoctoral Associate

E ryll@csail.mit.edu

55 News Results matching all criteria

AI & Machine Learning

November 08 '18

Why some Wikipedia disputes go unresolved

Study identifies reasons for unsettled editing disagreements and offers predictive tools that could improve deliberation.

Why some Wikipedia disputes go unresolved

AI & Machine Learning Robotics Health Care Transportation

November 01 '18

Fleets of drones could aid searches for lost hikers

System allows drones to cooperatively explore terrain under thick forest canopies where GPS signals are unreliable.

Fleets of drones could aid searches for lost hikers

Machines that learn language more like kids do 2

AI & Machine Learning Graphics & Vision Robotics

October 31 '18

Machines that learn language more like kids do

Computer model could improve human-machine interaction, provide insight into how children learn language.

Machines that learn language more like kids do

AI & Machine Learning Transportation

October 25 '18

Honda Research Institute Launches “Curious Minded Machine” Research Collaboration with MIT, University of Pennsylvania and University of Washington

Honda Research Institute USA seeks to develop intelligent systems that use curiosity to understand people’s needs and empower human capability through cross-disciplinary research that aims to advance breakthroughs in artificial cognition.

Honda Research Institute Launches “Curious Minded Machine” Research Collaboration with MIT, University of Pennsylvania and University of Washington

AI & Machine Learning Computational Biology Security & Cryptography Cybersecurity Health Care

October 18 '18

Cryptographic protocol enables greater collaboration in drug discovery

Neural network that securely finds potential drugs could encourage large-scale pooling of sensitive data.

Cryptographic protocol enables greater collaboration in drug discovery

AI & Machine Learning Health Care

October 17 '18

Automated system identifies dense tissue, a risk factor for breast cancer, in mammograms

Deep-learning model has been used successfully on patients, may lead to more consistent screening procedures.

Automated system identifies dense tissue, a risk factor for breast cancer, in mammograms

AI & Machine Learning

October 12 '18

AI Advances and Aspirations

October 12, 2018 - Eric Horvitz of Microsoft Research Labs gave a CSAIL seminar entitled "AI Advances and Aspirations."

AI Advances and Aspirations

AI & Machine Learning Computational Biology Health Care

October 04 '18

Regina Barzilay joins leadership of new effort on machine learning in health

MacArthur “geniuses” in machine learning and synthetic biology to serve as faculty co-leads; Nobel laureate to chair advisory board of new research center.

Regina Barzilay joins leadership of new effort on machine learning in health

model helps robots naviagte like humans 1

Algorithms & Theory AI & Machine Learning Robotics Transportation

October 04 '18

Model helps robots navigate more like humans do

In simulations, robots move through new environments by exploring, observing, and drawing from learned experiences.

Model helps robots navigate more like humans do

AI & Machine Learning Education Entertainment

October 04 '18

Detecting fake news at its source

Machine learning system aims to determine if an information outlet is accurate or biased.

Detecting fake news at its source

AI & Machine Learning Education Health Care Manufacturing Transportation Wireless

October 03 '18

Google AI’s Jeff Dean discusses using deep learning to solve challenging problems

Google AI’s Jeff Dean has a seemingly straightforward objective: he wants to use a collection of trainable mathematical units organized in layers to solve complicated tasks that will ultimately benefit many parts of society.

Google AI’s Jeff Dean discusses using deep learning to solve challenging problems

AI & Machine Learning Education Health Care Manufacturing Transportation Wireless

October 01 '18

Deep Learning to Solve Challenging Problems

October 1, 2018 - Jeff Dean of Google gave a CSAIL seminar titled "Deep Learning to Solve Challenging Problems."

Deep Learning to Solve Challenging Problems

Algorithms & Theory AI & Machine Learning Graphics & Vision Health Care

September 19 '18

Machine-learning system tackles speech and object recognition, all at once

Model learns to pick out objects within an image, using spoken descriptions.

Machine-learning system tackles speech and object recognition, all at once

Algorithms & Theory AI & Machine Learning Graphics & Vision Robotics

September 17 '18

Helping computers fill in the gaps between video frames

Machine learning system efficiently recognizes activities by observing how objects change in only a few key frames.

Helping computers fill in the gaps between video frames

AI & Machine Learning Education Entertainment

September 17 '18

“Hot Topics in Computing” series covers the spread of information and fake news

MIT professor Daniela Rus speaks on social media and misinformation spurred by global disasters with University of Washington professor Kate Starbird

“Hot Topics in Computing” series covers the spread of information and fake news

AI & Machine Learning Health Care

August 30 '18

Model can more naturally detect depression in conversations

Neural network learns speech patterns that predict depression in clinical interviews.

Model can more naturally detect depression in conversations

AI & Machine Learning Security & Cryptography

July 26 '18

CSAIL launches new initiative for financial technology

FinTech@CSAIL industry collaboration will work to improve business models, access to data, and security in the finance sector.

CSAIL launches new initiative for financial technology

Algorithms & Theory AI & Machine Learning Health Care

July 10 '18

Automating molecule design to speed up drug development

Machine-learning model could help chemists make molecules with higher potencies, much more quickly.

Automating molecule design to speed up drug development

AI & Machine Learning Graphics & Vision Entertainment

July 05 '18

An AI for editing music in videos

Given a video of a musical performance, CSAIL system can make specific instruments louder or softer

An AI for editing music in videos

Given an image of someone doing yoga, the system can generate an image of them doing golf (and vice versa)

AI & Machine Learning Graphics & Vision Education

June 18 '18

Put any person in any pose

MIT CSAIL neural network could be used by coaches to help players see themselves using the correct form

Put any person in any pose

AI & Machine Learning Graphics & Vision Health Care

June 12 '18

Artificial intelligence senses people through walls

Wireless smart-home system from the Computer Science and Artificial Intelligence Laboratory could monitor diseases and help the elderly “age in place.”

Artificial intelligence senses people through walls

Algorithms & Theory AI & Machine Learning Graphics & Vision Health Care

May 30 '18

Teaching chores to an artificial agent

Activity simulator could eventually teach robots tasks like making coffee or setting the table.

Teaching chores to an artificial agent

Algorithms & Theory AI & Machine Learning Robotics Transportation

May 23 '18

Making driverless cars change lanes more like human drivers do

Algorithm computes “buffer zones” around autonomous vehicles and reassess them on the fly.

Making driverless cars change lanes more like human drivers do

AI & Machine Learning Robotics Manufacturing

May 14 '18

Materials that can change size and shape by twisting

Approach opens up new possibilities for robots, spacecraft, and more

Materials that can change size and shape by twisting

24 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 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 Group

Clinical Decision-Making Group

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

+14

Peter Szolovits

Leads

Peter Szolovits

Research Areas

Impact Areas

Lead

Peter Szolovits

+14

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

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.

+17

Daniela Rus

Leads

Daniela Rus

Research Areas

Impact Areas

Lead

Daniela Rus

+17

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.

Patrick Winston

Leads

Patrick Winston

Research Areas

Impact Areas

Lead

Patrick Winston

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

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.

+10

Leslie Kaelbling

Tomas Lozano-Perez

Leads

Leslie Kaelbling

Tomas Lozano-Perez

Research Areas

Impact Areas

Lead

Leslie Kaelbling

Tomas Lozano-Perez

Leslie Kaelbling

Tomas Lozano-Perez

Research Group

Lecturers

Lecturers in CSAIL

Debayan Gupta

Leads

Debayan Gupta

Research Areas

Impact Areas

Lead

Debayan Gupta

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.

+10

Polina Golland

Leads

Polina Golland

Research Areas

Impact Areas

Lead

Polina Golland

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 focus on the 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.

+21

Jim Glass

Leads

Jim Glass

Research Areas

Impact Areas

Lead

Jim Glass

+21

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

Impact Areas

Lead

Gerald Sussman

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

Ruth Rosenholtz

Antonio Torralba

Research Areas

Impact Areas

Lead

Ted Adelson

Fredo Durand

John Fisher

William Freeman

Polina Golland

Eric Grimson

Berthold Horn

Aude Oliva

Ruth Rosenholtz

Antonio Torralba

62 Project Results

Project

3D Generative Adversarial Networks

Jiajun Wu

Leads

Jiajun Wu

Research Areas

Impact Areas

Learning and Intelligent Systems

Jiajun Wu

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.

Leads

Zi Wang

Leslie Kaelbling

Tomas Lozano-Perez

Research Areas

Impact Areas

Project

Adversarial Cyber Security

Una-May O'Reilly

Leads

Una-May O'Reilly

Research Areas

Impact Areas

Computer-Aided Programming

Una-May O'Reilly

Project

An Interlock for Self Driving Cars

Software Design Group

Self-driving cars are likely to be safer, on average, than human-driven cars. But they may fail in new and catastrophic ways that a human driver could prevent. This project is designing a new architecture for a highly dependable self-driving car.

Daniel Jackson

Armando Solar-Lezama

Leads

Daniel Jackson

Armando Solar-Lezama

Research Areas

Impact Areas

Interactive Robotics Group

Daniel Jackson

Armando Solar-Lezama

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

Arabic Language Processing

The Arabic language is spoken by over one billion people around the world. Arabic presents a variety of challenges for speech and language processing technologies. In our group, we have several research topics examining Arabic, including dialect identification, speech recognition, machine translation, and language processing.

Leads

Ramy Baly

Yonatan Belinkov

Mitra Mohtarami

Research Areas

Weiss Laboratory for Synthetic Biology

Project

Artificial tissue homeostasis

Leads

Research Areas

Impact Areas

Natural Language Processing Group

Project

Aspect-Augmented Adversarial Networks for Domain Adaptation

Regina Barzilay

Tommi Jaakkola

Leads

Regina Barzilay

Tommi Jaakkola

Research Areas

Regina Barzilay

Tommi Jaakkola

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.

Leads

Hao Tang

Wei-Ning Hsu

David Harwath

Tuka Al Hanai

Sameer Khurana

Di-Chia Chueh

Jim Glass

Research Areas

Impact Areas

Project

Autonomous Vehicle Databases

Database 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

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

Zi Wang

Stefanie Jegelka

Leads

Zi Wang

Stefanie Jegelka

Research Areas

Distributed Robotics Laboratory

Zi Wang

Stefanie Jegelka

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

Project

The Car Can Explain!

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

Leads

Gerald Sussman

Hal Abelson

Lalana Kagal

Daniel Weitzner

Research Areas

Impact Areas

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

Chest X-Ray Analysis

Medical Vision Group

We develop machine learning algorithms to automatically quantify the severity of pulmonary edema from chest x-rays.

Polina Golland

Leads

Polina Golland

Research Areas

Impact Areas

Polina Golland

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

Tristan Naumann

Elena Sergeeva

Peter Szolovits

Anna Rumshisky

Research Areas

Impact Areas

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

Clinical Note Representations That Predict ICU Mortality/Re-Admission

Our focus is on improving health-related outcomes by creating machine learning models that improve human risks.

Peter Szolovits

Leads

Peter Szolovits

Research Areas

Impact Areas

Peter Szolovits

Project

Community Question Answering