Research

Impact Areas
Research Areas

Filter options

9 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

5 Project Results

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

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

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

15 People Results

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

Azim Dehghani Amirabad

Postdoctoral Associate

Machine learning, Bioinformatics

E azimd@csail.mit.edu

Machine learning, Bioinformatics

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

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

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.

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.

1 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