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

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.

+10

Peter Szolovits

Leads

Peter Szolovits

Research Areas

Impact Areas

Manufacturing

Lead

Peter Szolovits

+10

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

Computer-Aided Programming

We develop techniques and tools that exploit automated reasoning and large amounts of computing power to tackle challenging programming problems

Armando Solar-Lezama

Leads

Armando Solar-Lezama

Research Areas

Impact Areas

Lead

Armando Solar-Lezama

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

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

Entertainment

Manufacturing

Lead

Stefanie Mueller

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

Programming Methodology Group

We develop innovative approaches for building software and for solving problems in modern parallel and distributed software systems.

Barbara Liskov

Leads

Barbara Liskov

Research Areas

Impact Areas

Lead

Barbara Liskov

Research Group

Software Design Group

Our goal is to find better ways to make software, and ways to make software better.

Daniel Jackson

Leads

Daniel Jackson

Research Areas

Impact Areas

Lead

Daniel Jackson

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

Impact Areas

Lead

Charles E. Leiserson

Neil Thompson

Charles E. Leiserson

Neil Thompson

Community of Research

Systems Community of Research

The Systems CoR is focused on building and investigating large-scale software systems that power modern computers, phones, data centers, and networks, including operating systems, the Internet, wireless networks, databases, and other software infrastructure.

+21

Sam Madden

Leads

Sam Madden

Research Areas

Impact Areas

Lead

Sam Madden

+21

Sam Madden

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

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

Impact Areas

Lead

Martin Rinard

Research Group

Visualization Group

We use visualization as a petri dish to study intelligence augmentation, or how can computational representations and software systems help amplify our cognition and creativity, while respecting our agency?

Arvind Satyanarayan

Leads

Arvind Satyanarayan

Research Areas

Impact Areas

Lead

Arvind Satyanarayan

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

Human-Computer Interaction Community of Research

26 Project Results

Project

Alloy

Software Design Group

Alloy is a language for describing structures and a tool for exploring them. It has been used in a wide range of applications from finding holes in security mechanisms to designing telephone switching networks. Hundreds of projects have used Alloy for design analysis, for verification, for simulation, and as a backend for many other kinds of analysis and synthesis tools, and Alloy is currently being taught in courses worldwide.

Daniel Jackson

Leads

Daniel Jackson

Research Areas

Weiss Laboratory for Synthetic Biology

Impact Areas

Daniel Jackson

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

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

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

Compression and Reordering for Parallel Graph Analytics

We plan to develop a suite of graph compression and reordering techniques as part of the Ligra parallel graph processing framework to reduce space usage and improve performance of graph algorithms.

Leads

Research Areas

Impact Areas

Project

Data Civilizer

Data scientists universally report that they spend at least 80% of their time finding data sets of interest, accessing them, cleaning them and assembling them into a unified whole.

Michael Stonebraker

Sam Madden

Leads

Michael Stonebraker

Sam Madden

Research Areas

Impact Areas

Michael Stonebraker

Sam Madden

Project

Data Warehouse Construction

Historically, DBMSs in the warehouse space partitioned their data across a shared nothing
cluster.

Michael Stonebraker

Leads

Michael Stonebraker

Research Areas

Impact Areas

Michael Stonebraker

Project

Determining Wikipedia's Influence on Science

Supertech Research Group

Wikipedia is one of the most widely accessed encyclopedia sites in the world, including by scientists. Our project aims to investigate just how far Wikipedia’s influence goes in shaping science.

Neil Thompson

Charles E. Leiserson

Leads

Neil Thompson

Charles E. Leiserson

Research Areas

Impact Areas

Distributed Robotics Laboratory

Neil Thompson

Charles E. Leiserson

Project

Distributed Robot Garden

The robot garden provides an aesthetically pleasing educational platform that can visualize computer science concepts and encourage young students to pursue programming and robotics.

Leads

Joseph DelPreto

Lindsay Sanneman

Daniela Rus

Research Areas

Robotics

Impact Areas

Entertainment

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

High-Performance Parallel Clustering

We are designing new parallel algorithms, optimizations, and frameworks for clustering large-scale graph and geometric data.

Julian Shun

Leads

Julian Shun

Research Areas

Impact Areas

Julian Shun

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

OpenTuner: An Extensible Framework for Program Autotuning

OpenTuner is a new framework for building domain-specific multi-objective program autotuners.

Leads

Research Areas

Impact Areas

Entertainment

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

Programming Systems Group

Project

Program Performance Prediction with Deep Learning

Predicting the number of clock cycles a processor takes to execute a block of assembly instructions in steady-state (the throughput) is important for both compiler designers and performance engineers.

However, building an analytical model to do so is especially complicated in modern x86-64 Complex Instruction Set Computer (CISC) machines with sophisticated processor microarchitectures in that it is tedious, error-prone, and must be performed from scratch for each processor generation.

Ithemal is the first tool that learns to predict the throughput of a set of instructions. It does so more accurately than state-of-the-art hand-written tools currently used in compiler backends and static machine code analyzers. In particular, Ithemal has less than half the error of state-of-the-art analytical models (LLVM's llvm-mca and Intel's IACA).

Leads

Research Areas

Impact Areas

Project

Programming Abstractions for Dynamic Graph Analytics

We plan to develop a programming abstraction to enable programmers to write efficient parallel programs to process dynamic graphs.

Julian Shun

Leads

Julian Shun

Research Areas

Impact Areas

Computational Connectomics Group

Julian Shun

Project

Reconstructing Neural Circuits from Mammalian Brain

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

Decentralized Information Group

Project

Solid: Social Linked Data

Computing & Society Community of Research

Solid aims to radically change the way Web applications work today, resulting in true data ownership as well as improved privacy.

Tim Berners-Lee

Lalana Kagal

Leads

Tim Berners-Lee

Lalana Kagal

Research Areas

Impact Areas

Internet of Things

Tim Berners-Lee

Lalana Kagal

Project

Starling: Query Optimization for Cloud Services

Starling is a scalable query execution engine built on cloud function services that computes at a fine granularity, helping people more easily match workload demand.

Sam Madden

Matthew Perron

Leads

Sam Madden

Matthew Perron

Research Areas

Impact Areas

Wireless

Sam Madden

Matthew Perron

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

Project

Tiramisu Compiler

A polyhedral compiler for expressing image processing, DNN, and linear/tensor algebra applications

Saman Amarasinghe

Leads

Saman Amarasinghe

Research Areas

Impact Areas

Saman Amarasinghe

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

Bonnie Berger

19 People Results

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

Saman Amarasinghe

Professor

Compilers, architectures, software engineering

E saman@csail.mit.edu

T 253-8879

Lead

Simit: A Language for Computing on Sparse Systems

Tiramisu Compiler

Member

Taco: The Tensor Algebra Compiler

Halide

OpenTuner: An Extensible Framework for Program Autotuning

Program Performance Prediction with Deep Learning

Covering All K-mers Using Joker Characters

Compilers, architectures, software engineering

PI
Core/Dual

Bonnie Berger

Professor

Computational biology, genomics

E bab@csail.mit.edu

T 253-1827

Lead

Towards Context-Aware Functional Genomics

Metagenomic Binning Through Low-Density Hashing

Computation and Biology

Member

Computation Structures Group

Programming Systems Group

Computational biology, genomics

PI
Core/Dual

Michael Carbin

Assistant Professor

Programming languages and systems.

E mcarbin@csail.mit.edu

T 253-5881

Lead

The Lottery Ticket Hypothesis

Member

Programming with spaces

Program Performance Prediction with Deep Learning

Programming languages and systems.

Azim Dehghani Amirabad

Postdoctoral Associate

Machine learning, Bioinformatics

E azimd@csail.mit.edu

Machine learning, Bioinformatics

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

Vision Group

Member

Computational Bounce Flash for Indoor Portraits

Halide

Visual Computing Community of Research

Vision, graphics, computational photography

Barış Ekim

Graduate Student

E ekim@csail.mit.edu

PI
Core/Dual

John Guttag

Professor

Machine learning, medicine, data-driven inference

E guttag@csail.mit.edu

T 253-6022

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

Computation Structures Group

Machine learning, medicine, data-driven inference

Jamey Hicks

Research Affiliate

E jamey.hicks@accelerated.tech

Member

PI
Core/Dual

Daniel Jackson

Professor

Software design, programming, systems

E dnj@csail.mit.edu

T 258-8471

Lead

Rethinking Software Design

Software Design Group

Gitless: a simple version control system built on top of Git

Déjà Vu: Constructing Apps from Concepts

Security by Design for Cyberphysical Systems

Poirot: Secure Protocol Implementation by Design

An Interlock for Self Driving Cars

Alloy

Wildcard

Member

Espalier

Human-Computer Interaction Community of Research

Computational Genomics Group

Wildcard

Software design, programming, systems

Konstantin Krismer

Graduate Student

E krismer@mit.edu

Member

Henry Lieberman

Research Scientist

Henry Lieberman is a Research Scientist at MIT CSAIL, in AI and HCI.

E lieber@MEDIA.MIT.EDU

Henry Lieberman is a Research Scientist at MIT CSAIL, in AI and HCI.

PI
Core/Dual

Arvind Satyanarayan

Assistant Professor

E arvindsatya@mit.edu

Lead

Visualization Group

Member

Center for Deployable Machine Learning (CDML)

Human-Computer Interaction Community of Research

PI
Core/Dual

Julian Shun

Assistant Professor

Parallel computing, applied algorithms, graph processing.

E jshun@mit.edu

T 258-0669

Lead

Programming Abstractions for Dynamic Graph Analytics

Bridging Theory and Practice in Shared-Memory Parallel Algorithm Design

High-Performance Parallel Clustering

Member

Computation Structures Group

Parallel computing, applied algorithms, graph processing.

Samuel Sledzieski

Graduate Student

E samsl@csail.mit.edu

PI
Core/Dual

Armando Solar-Lezama

Associate Professor

Programming languages, software analysis

E asolar@csail.mit.edu

T 258-9727

Lead

Synquid: Synthesis From Liquid Types

Computer-Aided Programming

An Interlock for Self Driving Cars

Member

Center for Deployable Machine Learning (CDML)

Computational Cognitive Science Group

Programming languages, software analysis

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