Research

Impact Areas

Lead

Justin Solomon

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

Community of Research

Vertical AI Community of Research

This CoR takes a unified approach to cover the full range of research areas required for success in artificial intelligence, including hardware, foundations, software systems, and applications.

Martin Rinard

Leads

Martin Rinard

Research Areas

Impact Areas

Lead

Martin Rinard

5 Project Results matching all criteria

Project

Deep Inverse Planning

Deep inverse planning for learning from high-dimensional demonstrations

Leads

Research Areas

Project

Reliable and Robust Machine Learning

Algorithms Group

We work towards a principled understanding of the current machine learning toolkit and making this toolkit be robust and reliable.

Aleksander Madry

Leads

Aleksander Madry

Research Areas

Impact Areas

Aleksander Madry

Project

Political Geometry: Establishing Fair Mathematical Standards for Political Redistricting

Gerrymandering is a direct threat to our democracy, undermining founding principles like equal protection under the law and eroding public confidence in elections.

Justin Solomon

Leads

Justin Solomon

Research Areas

Impact Areas

Justin Solomon

Project

Fast Lightweight Autonomy

The goal of the FLA program is to explore non-traditional perception and autonomy methods that could enable a new class of algorithms for minimalistic high-speed navigation in cluttered environments.

Nick Villanueva

Jake Ware

Leads

Jake Ware

Research Areas

Nick Villanueva

Jake Ware

Project

Geometry and topology for scientific computing and shape analysis

Developing state-of-the-art tools that process 3D surfaces and volumes

Justin Solomon

Leads

Justin Solomon

Research Areas

Impact Areas

Natural Language Processing Group

Justin Solomon

4 People Results matching all criteria

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

Applied Machine Learning Community of Research

Natural language processing, machine learning

PI
Core/Dual

Justin Solomon

Assistant Professor

Geometry, graphics, vision, machine learning, optimization.

E jsolomon@mit.edu

Lead

Geometry in Large-Scale Machine Learning

Political Geometry: Establishing Fair Mathematical Standards for Political Redistricting

Sensible Deep Learning for 3D Data

Optimal transport for statistics and machine learning

Geometry and topology for scientific computing and shape analysis

Member

Visual Computing Community of Research

Geometry, graphics, vision, machine learning, optimization.

Yu Wang

Graduate Student

E wangyu9@mit.edu

RM 32-D475A

Member

Geometry and topology for scientific computing and shape analysis

Gregory Wornell

Professor

Inference, learning, information theory, signal processing, imaging

E gww@mit.edu

T 253-3513

Inference, learning, information theory, signal processing, imaging

15 News Results matching all criteria

Algorithms & Theory AI & ML Graphics & Vision Big Data Transportation

October 29 '19

Deep learning with point clouds

Research aims to make it easier for self-driving cars, robotics, and other applications to understand the 3D world.

Deep learning with point clouds

Algorithms & Theory AI & ML Graphics & Vision Health Care

October 02 '19

Better fetal health - by building a map of the placenta

New technique stretches out MRI scans of placentas so they can be more accurately analyzed, and shows the potential of MRI for pregnancy monitoring.

Better fetal health - by building a map of the placenta

Algorithms & Theory AI & ML Graphics & Vision

August 22 '19

Why did my classifier just mistake a turtle for a rifle?

Two longtime friends explore how computer vision systems go awry.

Why did my classifier just mistake a turtle for a rifle?

Algorithms & Theory AI & ML Graphics & Vision Programming Languages & Software Engineering Systems & Networking Entertainment Manufacturing

August 05 '19

Computer-aided knitting

New CSAIL research uses machine learning to customize clothing designs

Computer-aided knitting

Algorithms & Theory Graphics & Vision Robotics Manufacturing

July 22 '19

Automated system generates robotic parts for novel tasks

When designing actuators involves too many variables for humans to test by hand, this system can step in.

Automated system generates robotic parts for novel tasks

Algorithms & Theory AI & ML Computational Biology Computer Architecture Graphics & Vision Human-Computer Interaction Programming Languages & Software Engineering Robotics Security & Cryptography Systems & Networking Cybersecurity Education Energy Entertainment Health Care Manufacturing Transportation Wireless

June 27 '19

CSAIL hosts first-ever TEDxMIT

Speakers — all women — discuss everything from gravitational waves to robot nurses

CSAIL hosts first-ever TEDxMIT

Algorithms & Theory AI & ML Graphics & Vision Energy Entertainment Manufacturing

December 10 '18

Teaching machines to see in 3-D

CSAIL’s approach uses algorithms and “2.5-D” sketches to let computers visualize images from any perspective

Teaching machines to see in 3-D

Algorithms & Theory Graphics & Vision Systems & Networking Health Care

November 29 '18

Higher-res models for creating structures with complex features

Computer scientists often develop mathematical models to understand how animals move, enabling breakthroughs in designing things like microrobotic wings and artificial bone structures.

Higher-res models for creating structures with complex features

Algorithms & Theory AI & ML 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 & ML 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

Algorithms & Theory AI & ML Graphics & Vision Entertainment

September 11 '18

Smoothing out sketches’ rough edges

MIT-developed tool improves automated image vectorization, saving digital artists time and effort.

Smoothing out sketches’ rough edges

Algorithms & Theory Graphics & Vision Robotics Manufacturing

September 10 '18

Robots can now pick up any object after inspecting it

Breakthrough CSAIL system suggests robots could one day be able to see well enough to be useful in people’s homes and offices.

Robots can now pick up any object after inspecting it

Algorithms & Theory AI & ML 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

Professor Berthold Horn and postdoctoral associate Liang Wang

Algorithms & Theory Graphics & Vision Transportation

December 14 '17

Improving traffic - by tailgating less

New CSAIL work shows that traffic would flow faster if drivers kept an equal distance between cars

Improving traffic - by tailgating less

System directs camera-equipped drones to maintain framing of an aerial shot.

Algorithms & Theory AI & ML Graphics & Vision Robotics Entertainment Transportation

May 17 '17

Cinematography on the fly

In recent years, a host of Hollywood blockbusters — including “The Fast and the Furious 7,” “Jurassic World,” and “The Wolf of Wall Street” — have included aerial tracking shots provided by drone helicopters outfitted with cameras. Those shots required separate operators for the drones and the cameras, and careful planning to avoid collisions. But a team of researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and ETH Zurich hope to make drone cinematography more accessible, simple, and reliable.

Cinematography on the fly

26 Group Results

Research Group

Algorithms Group

We devise new mathematical tools to tackle the increasing difficulty and importance of problems we pose to computers.

Leads

Costis Daskalakis

Erik Demaine

Michael Goemans

Piotr Indyk

David Karger

Jonathan Kelner

Tom Leighton

Charles E. Leiserson

Aleksander Madry

Ankur Moitra

Ronitt Rubinfeld

Nir Shavit

Ryan Williams

Virginia Vassilevska Williams

Research Areas

Impact Areas

Lead

Costis Daskalakis

Erik Demaine

Michael Goemans

Piotr Indyk

David Karger

Jonathan Kelner

Tom Leighton

Charles E. Leiserson

Aleksander Madry

Ankur Moitra

Ronitt Rubinfeld

Nir Shavit

Ryan Williams

Virginia Vassilevska Williams

Research Group

Applied Computing Group

We design software for high performance computing, develop algorithms for numerical linear algebra, and research random matrix theory and its applications.

Leads

Research Areas

Impact Areas

Wireless

Research Group

Broderick Lab

We work in the areas of statistics and machine learning.

Tamara Broderick

Leads

Tamara Broderick

Research Areas

Impact Areas

Lead

Tamara Broderick

Research Center

Center for Deployable Machine Learning (CDML)

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

Aleksander Madry

Leads

Aleksander Madry

Research Areas

Impact Areas

Lead

Aleksander Madry

Research Group

Complexity Theory Group

Our interests span quantum complexity theory, barriers to solving P versus NP, theoretical computer science with a focus on probabilistically checkable proofs (PCP), pseudo-randomness, coding theory, and algorithms.

Leads

Shafi Goldwasser

Ronitt Rubinfeld

Michael Sipser

Ryan Williams

Virginia Vassilevska Williams

Research Areas

Impact Areas

Lead

Shafi Goldwasser

Ronitt Rubinfeld

Michael Sipser

Ryan Williams

Virginia Vassilevska Williams

Research Group

Computation and Biology

Our lab focuses on designing algorithms to gain biological insights from advances in automated data collection and the subsequent large data sets drawn from them.

Bonnie Berger

Leads

Bonnie Berger

Research Areas

Impact Areas

Lead

Bonnie Berger

Research Group

Computational Connectomics Group

Our group’s goal is to create, based on such microscopic connectivity and functional data, new mathematical models explaining how neural tissue computes.

Nir Shavit

Leads

Nir Shavit

Research Areas

Impact Areas

Lead

Nir Shavit

Research Group

Computer Graphics Group

Our group focuses on synthetic image generation, computational photography, digital manufacturing, and geometry.

Leads

Fredo Durand

William Freeman

Wojciech Matusik

Justin Solomon

Research Areas

Impact Areas

Lead

Fredo Durand

William Freeman

Wojciech Matusik

Justin Solomon

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

Cryptography and Information Security Group

We seek to develop techniques for securing tomorrow's global information infrastructure by exploring theoretical foundations, near-term practical applications, and long-range speculative research.

Leads

Shafi Goldwasser

Silvio Micali

Ronald Rivest

Vinod Vaikuntanathan

Butler Lampson

Research Areas

Impact Areas

Wireless

Lead

Shafi Goldwasser

Silvio Micali

Ronald Rivest

Vinod Vaikuntanathan

Butler Lampson

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

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

Manufacturing

Lead

Stefanie Mueller

Research Group

Lecturers

Lecturers in CSAIL

Leads

Research Areas

Impact Areas

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

Multicore Algorithmics

We develop techniques for designing, implementing, and reasoning about multiprocessor algorithms, in particular concurrent data structures for multicore machines and the mathematical foundations of the computation models that govern their behavior.

Nir Shavit

Leads

Nir Shavit

Research Areas

Impact Areas

Lead

Nir Shavit

Research Group

Multimodal Understanding Group

Our objective is to build techniques, software, and hardware that enable natural interaction with
computation.

Randall Davis

Leads

Randall Davis

Research Areas

Impact Areas

Lead

Randall Davis

Research Group

Quantum Information Science Group

Our research interests center around the capabilities and limits of quantum computers, and computational complexity theory more generally.

Peter Shor

Leads

Peter Shor

Research Areas

Impact Areas

Lead

Peter Shor

Research Group

Sensing, Learning and Inference

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

John Fisher

Leads

John Fisher

Research Areas

Impact Areas

Internet of Things

Lead

John Fisher

Research Group

Supertech Research Group

We investigate the technologies that support scalable high-performance computing, including hardware, software, and theory.

Charles E. Leiserson

Neil Thompson

Leads

Charles E. Leiserson

Neil Thompson

Research Areas

Computer Architecture

Impact Areas

Lead

Charles E. Leiserson

Neil Thompson

Charles E. Leiserson

Neil Thompson

Community of Research

Theory of Computation Community of Research

The goal of the Theory of Computation CoR is to study the fundamental strengths and limits of computation as well as how these interact with mathematics, computer science, and other disciplines.

+20

Costis Daskalakis

Leads

Costis Daskalakis

Research Areas

Impact Areas

Lead

Costis Daskalakis

+20

Costis Daskalakis

Research Group

Theory of Distributed Systems Group

We work on a wide range of problems in distributed computing theory. We study algorithms and lower bounds for typical problems that arise in distributed systems---like resource allocation, implementing shared memory abstractions, and reliable communication.

Nancy Lynch

Leads

Nancy Lynch

Research Areas

Impact Areas

Lead

Nancy Lynch

Community of Research

Vertical AI Community of Research

This CoR takes a unified approach to cover the full range of research areas required for success in artificial intelligence, including hardware, foundations, software systems, and applications.

Martin Rinard

Leads

Martin Rinard

Research Areas

Impact Areas

Lead

Martin Rinard

105 Project Results

Project

3D Generative Adversarial Networks

Cognitive AI Community of Research

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

Computational Cognitive Science Group

Impact Areas

Manufacturing

Project

A Counterfactual Simulation Model of Causal Judgment

Cognitive AI Community of Research

We develop a computational model that explains how people make causal judgments in physical scenes by mentally simulating counterfactual outcomes and comparing those to what actually happened.

Leads

Research Areas

Impact Areas

Computation Structures Group

Project

A new way of handling all-to-all broadcast

We design a new all-to-all broadcasts scheme with significantly less communication cost using aggregate signatures.

Alin Tomescu

Jun Wan

Leads

Jun Wan

Research Areas

Alin Tomescu

Jun Wan

Project

A Simplified and Extensible Cilk Runtime for Research

CilkS is a new runtime system for the Cilk multithreaded programming environment which makes it easy to experiment with new algorithms, data structures, and programming linguistics.

Charles E. Leiserson

Tao Schardl

Leads

Charles E. Leiserson

Tao Schardl

Research Areas

Learning and Intelligent Systems

Charles E. Leiserson

Tao Schardl

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

Imagination, Computation, and Expression Laboratory (ICE Lab)

Leslie Kaelbling

Tomas Lozano-Perez

Project

AIRvatar System: A Framework for Analyzing Virtual Identities

Human-Computer Interaction Community of Research

AIRvatar is a system that telemetrically collects and analyzes fine-grained data on users’ virtual identities and the process used to create them.

D. Fox Harrell

Leads

D. Fox Harrell

Research Areas

Impact Areas

D. Fox Harrell

Project

Algebraic Techniques for Algorithm Design

We work on improving the algorithms for algebraic problems like matrix multiplication, and using these to design algorithms for fundamental non-algebraic problems.

Virginia Vassilevska Williams

Leads

Virginia Vassilevska Williams

Research Areas

Virginia Vassilevska Williams

Project

Algorithmic Aspects of Performance Engineering

Supertech Research Group

The project concerns algorithmic solutions for writing fast codes.

Leads

Research Areas

Impact Areas

Theory of Distributed Systems Group

Wireless

Project

An Algorithmic Theory of Brain Networks

We are developing an algorithmic theory for brain networks, based on simple synchronized stochastic graph-based neural network models.

Nancy Lynch

Leads

Nancy Lynch

Research Areas

Nancy Lynch

Project

Analyzing Player Profile Data

Developing new methods for analyzing large quantities of player profile data, such as hundreds of thousands of profile images or chat logs.

D. Fox Harrell

Peter Mawhorter

Leads

D. Fox Harrell

Peter Mawhorter

Research Areas

D. Fox Harrell

Peter Mawhorter

Project

Approximating the diameter of a directed graph

There is a family of approximation algorithms for computing the diameter of an undirected graph that give a time/accuracy trade-off and our goal is to extend these results to directed graphs.

Virginia Vassilevska Williams

Leads

Virginia Vassilevska Williams

Research Areas

Virginia Vassilevska Williams

Project

Artificial Co-driver

By observing driver in real road situations, we learn a computer assistant that can make driving easier, safer and more enjoyable.

Leads

Research Areas

Natural Language Processing Group

Impact Areas

Transportation

Project

Aspect-Augmented Adversarial Networks for Domain Adaptation

Vertical AI Community of Research

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

Cryptography and Information Security Group

Regina Barzilay

Tommi Jaakkola

Project

Basing Cryptography on Structured Hardness

We aim to base a variety of cryptographic primitives on complexity theoretic assumptions. We focus on the assumption that there exist highly structured problems --- admitting so called "zero-knowledge" protocols --- that are nevertheless hard to compute

Leads

Research Areas

Learning and Intelligent Systems

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

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

Transportation

Project

Blood Pressure Imager

Development of affordable wearable continuous blood pressure monitor based on radial arterial pulse imaged from the skin surface of human wrist

Mumin Jin

Aya G. Halawi

Jianhua Li

Leads

Abhijit Biswas

Ted Adelson

Mandayam A. Srinivasan

Mohan Thanikachalam

Research Areas

Mumin Jin

Aya G. Halawi

Jianhua Li

Project

Bridging Theory and Practice in Shared-Memory Parallel Algorithm Design

This project aims to design parallel algorithms for shared-memory machines that are efficient both in theory and also in practice.

Julian Shun

Leads

Julian Shun

Research Areas

Impact Areas

Julian Shun

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

Characterizing the Sensitivity of Vision-in-the-Loop Driving Controllers Using CG

We work on understanding and improving vision algorithms used for self driving cars, by introducing synthetic data-sets to the loop.

Leads

Research Areas

Impact Areas

Transportation

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

Computational Bounce Flash for Indoor Portraits

To achieve high-quality photo lighting in challenging environments, our prototype camera dynamically reconstructs a 3D scene model and directs a motor-controlled flash head at nearby walls and ceilings for soft indirect illumination.

Lukas Murmann

Leads

Lukas Murmann

Research Areas

Impact Areas