Research

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 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

Robotics

Security & Cryptography

Impact Areas

Lead

Aleksander Madry

Research Group

Clinical Decision-Making Group

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

+11

Peter Szolovits

Leads

Peter Szolovits

Research Areas

Impact Areas

Manufacturing

Lead

Peter Szolovits

+11

Peter Szolovits

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 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

Impact Areas

Lead

Manolis Kellis

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 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

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

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

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

Sensing, Learning and Inference

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

John Fisher

Leads

John Fisher

Research Areas

Robotics

Impact Areas

Energy

Internet of Things

Lead

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

Security & Cryptography

Impact Areas

Lead

Costis Daskalakis

+20

Costis Daskalakis

Research Group

Tidor Lab

We focus on the analysis of complex biological systems at both the molecular level and the systems level.

Bruce Tidor

Leads

Bruce Tidor

Research Areas

Impact Areas

Lead

Bruce Tidor

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

Security & Cryptography

Impact Areas

Lead

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

Impact Areas

Entertainment

Transportation

Lead

Ted Adelson

Fredo Durand

John Fisher

William Freeman

Polina Golland

Berthold Horn

Aude Oliva

Antonio Torralba

Eric Grimson

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

Computational Cognitive Science Group

23 Project Results

Project

A Counterfactual Simulation Model of Causal Judgment

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

Weiss Laboratory for Synthetic Biology

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

Cardiac MRI analysis

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

Clinical Intervention Prediction with Neural Networks

Applied Machine Learning Community of Research

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

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

Computational Design and Fabrication Group

Polina Golland

Project

Crowdsourcing in Graphics and Vision

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

Impact Areas

Entertainment

Alexandre Kaspar

Project

Drug Target Identification Via Computational Modeling

Tidor Lab

We use computational models of biological pathways in disease to estimate the range of possible responses to various hypothetical drugs, given patient variability and limited pathway-relevant data.

Leads

Research Areas

Impact Areas

Weiss Laboratory for Synthetic Biology

Project

Flexible cellular platforms for reconfigurable biocircuits

Existing methods for cloning and recombination of DNA enable construction of arbitrary sequences. However, the sequential nature of these techniques makes them time-consuming and expensive. Furthermore, while the transformation of an existing plasmid into a host strain can be reliable when a selection marker is used, there are many current limitations: the number of different plasmids that can be co-transformed is limited by the choice of markers and compatible origins of replication; plasmids are less stable than chromosomal DNA and are difficult to maintain indefinitely without mutation; and cistronic interactions cannot be designed since each new nucleotide sequence added is on an unconnected DNA molecule. To overcome these limitations, we are designing reconfigurable chromosomes consisting of both fixed and variable regions. While the fixed region is carefully optimized and tuned ahead of time, the variable region can be modified in the field, at the point-of-use, leading to rapid and on-demand realization of novel biocircuits with many different phenotypes.

Leads

Research Areas

Impact Areas

Project

Geometry and topology for scientific computing and shape analysis

Computer Graphics Group

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

Justin Solomon

Leads

Justin Solomon

Research Areas

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

Impact Areas

Internet of Things

Justin Solomon

Stefanie Jegelka

Project

Metagenomic Binning Through Low-Density Hashing

Our goal is to develop better metagenomic binning by origin species of fragments of sequenced environmental DNA.

Bonnie Berger

Leads

Bonnie Berger

Research Areas

Impact Areas

Bonnie Berger

Project

Monitoring Fetal Health

We develop algorithms for fetal MRI interpretation, to enable noninvasive fetal monitoring from MRI.

Polina Golland

Leads

Polina Golland

Research Areas

Impact Areas

Polina Golland

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

Population-level Tumor Growth Inhibition Modeling

Tidor Lab

We develop, parameterize, and validate a model for tumor growth inhibition using in vivo mouse data and study the effects of modeling uncertainty and inter-individual variability on drug candidate efficacy predictions.

Leads

Research Areas

Impact Areas

Project

Quantification of Pulmonary Edema in Chest Radiographs

We develop machine learning algorithms to automatically and quantitatively assess the severity of pulmonary edema from chest x-ray images.

Polina Golland

Leads

Polina Golland

Research Areas

Impact Areas

Computational Connectomics Group

Polina Golland

Project

Reconstructing Neural Circuits from Mammalian Brain

Theory of Computation Community of Research

We develop algorithms, systems and software architectures for automating reconstruction of accurate representations of neural tissue structures, such as nanometer-scale neurons' morphology and synaptic connections in the mammalian cortex.

Yaron Meirovitch

Nir Shavit

Leads

Yaron Meirovitch

Nir Shavit

Research Areas

Impact Areas

Clinical Decision-Making Group

Yaron Meirovitch

Nir Shavit

Project

Semi-Supervised Regression with Cycle Wasserstein Regression GANs

Using adversarial signals and a cycle-consistency based regularization, we can supplement paired regression tasks with unpaired data to improve regression performance.

Leads

Research Areas

Impact Areas

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

Manufacturing

Justin Solomon

Project

Structure-based Inhibitor Design Against ZIKV Protease

Tidor Lab

This project uses computational biology and chemistry tools to design a pharmaceutical to combat the Zika Virus.

Leads

Research Areas

Impact Areas

Theory of Computation Community of Research

Project

Towards Context-Aware Functional Genomics

Computation and Biology

We aim to develop a context-aware data-driven functional genomics framework that can characterize tissue-specific gene representations, provide context-aware genotype to phenotype mapping, and enable network-based exploration of disease genetics.

Bonnie Berger

Leads

Bonnie Berger

Research Areas

Impact Areas

Clinical Decision-Making Group

Bonnie Berger

Project

Using Clinical Domain Knowledge for Processing Physiological Data

Using medical knowledge to improve learned representations of patient health trajectories.

Leads

Research Areas

Impact Areas

Distributed Robotics Laboratory

Project

Wearable Blind Navigation

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

Leads

Research Areas

Robotics

Impact Areas

Transportation

Project

Where Are They Looking?

Our goal is to build a system that predicts where people are looking in images. Given an image and the location of a head, our approach follows the gaze of the person and identifies the object being looked at.

Leads

Research Areas

Impact Areas

Entertainment

27 People Results

Mazdak Abulnaga

Graduate Student

medical vision

E abulnaga@mit.edu

Member

Geometry and topology for scientific computing and shape analysis

medical vision

PI
Core/Dual

Ted Adelson

Professor

Vision, touch sensing, robotics

E adelson@csail.mit.edu

T 253-0645

Lead

Embodied Intelligence Community of Research

Blood Pressure Imager

Member

Natural Language Processing Group

Vision, touch sensing, robotics

Leandro Agudelo

Research Scientist

Systems Genomics, CompBio, Topological Integrative Biology, Biology

E lagudelo@csail.mit.edu

Systems Genomics, CompBio, Topological Integrative Biology, Biology

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

Bonnie Berger

Professor

Computational biology, genomics

E bab@csail.mit.edu

T 253-1827

Lead

Covering All K-mers Using Joker Characters

Towards Context-Aware Functional Genomics

Metagenomic Binning Through Low-Density Hashing

Computation and Biology

Member

Computation Structures Group

Theory of Computation Community of Research

Applied Machine Learning Community of Research

Computational biology, genomics

Yu-An Chung

Graduate Student

Speech and language processing, machine learning

E andyyuan@mit.edu

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

Clinical Neuroimaging

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

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

Lead

Sensing, Learning and Inference

Member

Vision, machine learning, signal processing

PI
Core/Dual

Polina Golland

Professor

Vision, medical imaging, statistical inference

E polina@csail.mit.edu

T 253-8005

Lead

Quantification of Pulmonary Edema in Chest Radiographs

Cardiac MRI analysis

Clinical Neuroimaging

Member

Data-Driven Inference Group

Vision, medical imaging, statistical inference

PI
Core/Dual

John Guttag

Professor

Machine learning, medicine, data-driven inference

E guttag@csail.mit.edu

T 253-6022

Lead

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

Fern Keniston

Senior Administrative Assistant

Research and Education Support

E fern@csail.mit.edu

T 253-5860

RM 32/ 32-250A/ 391

Member

Clinical Decision-Making Group

Research and Education Support

Konstantin Krismer

Graduate Student

E krismer@mit.edu

Member

Computational Genomics Group

PI
Core/Dual

John Leonard

Professor

Robotics, navigation/mapping, self-driving cars

E jleonard@csail.mit.edu

T 253-5305

Lead

Marine Robotics Group

Self-Driving Vehicles

Member

Embodied Intelligence Community of Research

Robotics, navigation/mapping, self-driving cars

Ruizhi Liao

Graduate Student

E ruizhi@mit.edu

Member

Quantification of Pulmonary Edema in Chest Radiographs

Razvan Marinescu

Postdoctoral Associate

Postdoctoral Associate working with Polina Golland on neuroimaging.

E razvan@csail.mit.edu

RM 32-D475B

Member

Clinical Neuroimaging

Postdoctoral Associate working with Polina Golland on neuroimaging.

Nalini Singh

Graduate Student

E nmsingh@mit.edu

RM 32-D475B

Member

Samuel Sledzieski

Graduate Student

E samsl@csail.mit.edu

Dmitriy Smirnov

Graduate Student

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

E smirnov@mit.edu

RM 32-D475B

Member

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

Lead

Computer Graphics 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

Computational Cognitive Science Group

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

Member

Center for Brains, Minds and Machines

Single-Image 3D Interpreter Network

3D Generative Adversarial Networks

Embodied Intelligence Community of Research