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11 Group Results

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.

+5

Aleksander Madry

Leads

Aleksander Madry

Research Areas

Algorithms & Theory

Graphics & Vision

Human-Computer Interaction

Programming Languages & Software Engineering

Security & Cryptography

Impact Areas

Lead

Aleksander Madry

Aleksander Madry

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

Algorithms & Theory

Computational Biology

Impact Areas

Lead

Bonnie Berger

Bonnie Berger

Research Group

Computational Biology Group

We seek to understand the mechanistic basis of human disease, using a combination of computational and experimental techniques.

Manolis Kellis

Leads

Manolis Kellis

Research Areas

Computational Biology

Impact Areas

Lead

Manolis Kellis

Manolis Kellis

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

Algorithms & Theory

Computational Biology

Impact Areas

Lead

Nir Shavit

Nir Shavit

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

Computational Biology

Impact Areas

Lead

Aude Oliva

Aude Oliva

Research Group

Geometric Data Processing Group

Our group studies geometric problems in computer graphics, computer vision, machine learning, optimization, and other disciplines.

+6

Justin Solomon

Leads

Justin Solomon

Research Areas

Algorithms & Theory

Graphics & Vision

Impact Areas

Lead

Justin Solomon

Justin Solomon

Research Group

Sensing, Learning and Inference

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

+6

John Fisher

Leads

John Fisher

Research Areas

Graphics & Vision

Impact Areas

Internet of Things

Lead

John Fisher

John Fisher

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

Algorithms & Theory

Computational Biology

Programming Languages & Software Engineering

Security & Cryptography

Impact Areas

Lead

Costis Daskalakis

Costis Daskalakis

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.

+7

Martin Rinard

Leads

Martin Rinard

Research Areas

Algorithms & Theory

Graphics & Vision

Programming Languages & Software Engineering

Security & Cryptography

Systems & Networking

Impact Areas

Internet of Things

Lead

Martin Rinard

Martin Rinard

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

Berthold Horn

Aude Oliva

Antonio Torralba

Eric Grimson

Research Areas

Graphics & Vision

Impact Areas

Lead

Ted Adelson

Fredo Durand

John Fisher

William Freeman

Polina Golland

Berthold Horn

Aude Oliva

Antonio Torralba

Eric Grimson

Community of Research

Visual Computing Community of Research

The shared mission of Visual Computing is to connect images and computation, spanning topics such as image and video generation and analysis, photography, human perception, touch, applied geometry, and more.

+10

Ruth Rosenholtz

Leads

Ruth Rosenholtz

Research Areas

Graphics & Vision

Impact Areas

Lead

Ruth Rosenholtz

Ruth Rosenholtz

11 Project Results

Project

Artificial Co-driver

Computer Graphics Group

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

Leads

Research Areas

Graphics & Vision

Impact Areas

Project

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

Computer Graphics Group

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

Leads

Research Areas

Graphics & Vision

Impact Areas

Project

Computational Multicopter Design

Computer Graphics Group

A system that can help you to design our own drone!

Tao Du

Leads

Tao Du

Research Areas

Graphics & Vision

Impact Areas

Tao Du

Project

Crowdsourcing in Graphics and Vision

Computational Design and Fabrication Group

Our goal is to develop new applications and algorithms that leverage the skills of distributed crowdworkers, notably for image and video processing applications.

Alexandre Kaspar

Leads

Alexandre Kaspar

Research Areas

Graphics & Vision

Human-Computer Interaction

Impact Areas

Alexandre Kaspar

Project

Driver-Friendly Bilateral Control for Suppressing Traffic Instabilities

We are studying how best to implement bilateral control and make it acceptable to drivers

Berthold Horn

Leads

Berthold Horn

Research Areas

Graphics & Vision

Systems & Networking

Impact Areas

Berthold Horn

Project

Geometry and topology for scientific computing and shape analysis

Geometric Data Processing Group

Computer Graphics Group

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

+1

Justin Solomon

Leads

Justin Solomon

Research Areas

Algorithms & Theory

Graphics & Vision

Impact Areas

Justin Solomon

Project

Geometry in Large-Scale Machine Learning

Machine Learning

Data often has geometric structure which can enable better inference; this project aims to scale up geometry-aware techniques for use in machine learning settings with lots of data, so that this structure may be utilized in practice.

Justin Solomon

Stefanie Jegelka

Leads

Justin Solomon

Stefanie Jegelka

Research Areas

Graphics & Vision

Impact Areas

Internet of Things

Justin Solomon

Stefanie Jegelka

Project

Peripheral Vision and Driver Behavior

Our goal is to understand what drivers can perceive when they are not attending to the road ahead and the consequences of their perceptions for safety.

Leads

Research Areas

Graphics & Vision

Impact Areas

Project

Political Geometry: Establishing Fair Mathematical Standards for Political Redistricting

Geometric Data Processing Group

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

Algorithms & Theory

Graphics & Vision

Human-Computer Interaction

Impact Areas

Justin Solomon

Project

Sensible Deep Learning for 3D Data

Geometric Data Processing Group

Machine Learning

Developing state-of-the-art deep learning algorithms for analyzing and modeling 3D geometry

Justin Solomon

Leads

Justin Solomon

Research Areas

Graphics & Vision

Impact Areas

Justin Solomon

Project

Wearable Blind Navigation

Distributed Robotics Laboratory

We enable independent navigation for visually impaired users through a wearable feedback system using time-of-light sensors or depth cameras.

Leads

Research Areas

Graphics & Vision

Human-Computer Interaction

Impact Areas

21 People Results

PI
Core/Dual

Ted Adelson

Professor

Vision, touch sensing, robotics

E adelson@csail.mit.edu

T 253-0645

RM

Lead

Blood Pressure Imager

Embodied Intelligence Community of Research

Member

Visual Computing Community of Research

Vision, touch sensing, robotics

PI
Core/Dual

Regina Barzilay

Professor

Natural language processing, machine learning

E regina@csail.mit.edu

T 258-5706

RM

Lead

Natural Language Processing Group

Aspect-Augmented Adversarial Networks for Domain Adaptation

Member

Vertical AI Community of Research

Applied Machine Learning Community of Research

Natural language processing, machine learning

Yu-An Chung

Graduate Student

Speech and language processing, machine learning

E andyyuan@mit.edu

RM

Lead

Unsupervised Speech Processing

Member

Spoken Language Systems Group

Speech and language processing, machine learning

Adrian Dalca

Research Scientist

E adalca@csail.mit.edu

Member

Medical Vision Group

Clinical Neuroimaging

Mustafa Doga Dogan

Graduate Student

E doga@mit.edu

RM

Member

HCI Engineering Group

PI
Core/Dual

Fredo Durand

Professor

Vision, graphics, computational photography

E fredo@csail.mit.edu

T 253-7223

RM

Lead

Computer Graphics Group

Human-Computer Interaction

Computational Understanding of Visualizations and Graphic Designs

Member

Computational Bounce Flash for Indoor Portraits

Visual Computing Community of Research

Vision, graphics, computational photography

Barış Ekim

Graduate Student

E ekim@csail.mit.edu

PI
Core/Dual

John Fisher

Senior Research Scientist

Vision, machine learning, signal processing

E fisher@csail.mit.edu

T 253-0788

RM

Lead

Sensing, Learning and Inference

Member

Visual Computing Community of Research

Vision, machine learning, signal processing

PI
Core/Dual

William Freeman

Professor

Vision, machine learning, Bayesian modeling

E billf@csail.mit.edu

T 253-8828

RM

Lead

Computer Graphics Group

Member

Single-Image 3D Interpreter Network

Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks

Learning the Arrow of Time from Videos

3D Generative Adversarial Networks

Embodied Intelligence Community of Research

Visual Computing Community of Research

Vision, machine learning, Bayesian modeling

PI
Core/Dual

John Guttag

Professor

Machine learning, medicine, data-driven inference

E guttag@csail.mit.edu

T 253-6022

RM

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

Evan Hernandez

Graduate Student

Natural language processing, machine learning, interpretability

E dez@mit.edu

Natural language processing, machine learning, interpretability

PI
Core/Dual

Berthold Horn

Professor

Vision, computational imaging

E bkph@csail.mit.edu

T 253-5863

RM

Lead

Driver-Friendly Bilateral Control for Suppressing Traffic Instabilities

Member

Visual Computing Community of Research

Vision, computational imaging

Konstantin Krismer

Graduate Student

E krismer@mit.edu

RM

Member

Computational Genomics Group

PI
Core/Dual

John Leonard

Professor

Robotics, navigation/mapping, self-driving cars

E jleonard@csail.mit.edu

T 253-5305

RM

Lead

Marine Robotics Group

Self-Driving Vehicles

Member

Embodied Intelligence Community of Research

Robotics, navigation/mapping, self-driving cars

Dmitriy Smirnov

Graduate Student

https://people.csail.mit.edu/smirnov/

E smirnov@mit.edu

RM 32-D475B

Member

Geometric Data Processing Group

Sensible Deep Learning for 3D Data

https://people.csail.mit.edu/smirnov/

PI
Core/Dual

Justin Solomon

Assistant Professor

Geometry, graphics, vision, machine learning, optimization.

E jsolomon@mit.edu

RM

Lead

Computer Graphics Group

Geometric Data Processing Group

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.

Joshua Tenenbaum

Professor

Computational cognitive science, machine learning

E jbt@csail.mit.edu

T 452-2010

RM 46-4015

Lead

Computational Cognitive Science Group

Member

Center for Brains, Minds and Machines

Single-Image 3D Interpreter Network

3D Generative Adversarial Networks

Embodied Intelligence Community of Research

Cognitive AI Community of Research

Visual Computing Community of Research

Computational cognitive science, machine learning

Neil Thompson

Research Scientist

I'm an innovation scholar studying computer science and economics.

E neil_t@mit.edu

RM

Lead

Supertech Research Group

Determining Wikipedia's Influence on Science

I'm an innovation scholar studying computer science and economics.

PI
Core/Dual

Antonio Torralba

Professor

Vision, graphics, perception, machine learning

E torralba@csail.mit.edu

T 324-0900

RM 32-386G

Lead

Understanding Light via Deep Neural Networks

Understandable Deep Networks

Understanding Food images

Member

Predictive Vision

Where Are They Looking?

Single-Image 3D Interpreter Network

VirtualHome: Representing Activities as Programs

Places Database for Scene Recognition

Semantic Scene Understanding through ADE20K dataset

Crossing the Vision-Language Boundary

Center for Deployable Machine Learning (CDML)

Visual Computing Community of Research

Embodied Intelligence Community of Research

Vision, graphics, perception, machine learning

Yu Wang

Graduate Student

E wangyu9@mit.edu

RM 32-D475A

Member

Geometric Data Processing Group

Geometry and topology for scientific computing and shape analysis

Paul Zhang

Graduate Student

I study meshing, PDE and manifold constrained optimization.

E pzpzpzp1@mit.edu

RM

Member

Geometric Data Processing Group

Geometry and topology for scientific computing and shape analysis

I study meshing, PDE and manifold constrained optimization.

6 News Results

point cloud 1

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

Barbara Liskov 2

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

self driving

AI & ML Graphics & Vision Robotics Transportation

May 07 '18

Self-driving cars for country roads

For all the progress made in self-driving technologies, there still aren’t many places where they can actually drive. Companies like Google only test their fleets in major cities where they’ve spent countless hours meticulously labeling the exact 3-D positions of lanes, curbs, off-ramps, and stop signs.

Self-driving cars for country roads

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

A new system from MIT's Computer Science and Artificial Intelligence Laboratory works by analyzing light at the edge of walls, which is impacted by the reflections of objects around the corner from the camera.

AI & ML Graphics & Vision Transportation

October 09 '17

An algorithm for your blind spot

Light lets us see the things that surround us, but what if we could also use it to see things hidden around corners? It sounds like science fiction, but that’s the idea behind a new algorithm out of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) — and its discovery has implications for everything from emergency response to self-driving cars.

An algorithm for your blind spot

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