Research

Impact Areas

Lead

Sam Madden

+21

Sam Madden

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

Graphics & Vision

Impact Areas

Lead

Martin Rinard

2 Project Results matching all criteria

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

Impact Areas

Daniel Jackson

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

Sam Madden

Matthew Perron

14 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.

Aleksander Madry

Leads

Aleksander Madry

Research Areas

Graphics & Vision

Robotics

Impact Areas

Lead

Aleksander Madry

Research Group

Commit Group

We focus on finding novel approaches to improve the performance of modern computer systems without unduly increasing the complexity faced by application developers, compiler writers, or computer architects.

Saman Amarasinghe

Leads

Saman Amarasinghe

Research Areas

Impact Areas

Lead

Saman Amarasinghe

Research Group

Computation Structures Group

Our mission is fostering the creation and development of high-performance, reliable and secure computing systems that are easy to interact with.

+21

Leads

Srini Devadas

Daniel Sanchez

Armando Solar-Lezama

Arvind

Research Areas

Impact Areas

Lead

Srini Devadas

Daniel Sanchez

Armando Solar-Lezama

Arvind

+21

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

Data Systems Group

We conduct research on all areas of database systems and information management.

+15

Leads

Sam Madden

Michael Stonebraker

Tim Kraska

Research Areas

Impact Areas

Lead

Sam Madden

Michael Stonebraker

Tim Kraska

+15

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

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

+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

Computational Biology

Impact Areas

Lead

Costis Daskalakis

+20

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.

Martin Rinard

Leads

Martin Rinard

Research Areas

Graphics & Vision

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

12 Project Results

Project

Alloy

Software Design Group

Daniel Jackson

Leads

Daniel Jackson

Research Areas

Impact Areas

Daniel Jackson

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

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

Neil Thompson

Charles E. Leiserson

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

Programming Systems Group

Julian Shun

Project

Program Performance Prediction with Deep Learning

Commit Group

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

Julian Shun

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

Sam Madden

Matthew Perron

Project

Tiramisu Compiler

Commit Group

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

Video Data Querying

We are developing machine-learning technology to help users efficiently run data queries over large archives of raw video.

Sam Madden

Favyen Bastani

Leads

Sam Madden

Favyen Bastani

Research Areas

Impact Areas

Simit: A Language for Computing on Sparse Systems

Entertainment

Transportation

Sam Madden

Favyen Bastani

10 People Results

PI
Core/Dual

Saman Amarasinghe

Professor

Compilers, architectures, software engineering

E saman@csail.mit.edu

T 253-8879

Lead

Commit Group

Tiramisu Compiler

Member

Taco: The Tensor Algebra Compiler

Halide

OpenTuner: An Extensible Framework for Program Autotuning

Program Performance Prediction with Deep Learning

Programming Systems Group

Compilers, architectures, software engineering

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

Applied Machine Learning Community of Research

Systems Community of Research

Programming languages and systems.

Jamey Hicks

Research Affiliate

E jamey.hicks@accelerated.tech

Member

Computation Structures Group

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

Systems Community of Research

Wildcard

Software design, programming, systems

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)

Programming Abstractions for Dynamic Graph Analytics

PI
Core/Dual

Julian Shun

Assistant Professor

Parallel computing, applied algorithms, graph processing.

E jshun@mit.edu

T 258-0669

Lead

Bridging Theory and Practice in Shared-Memory Parallel Algorithm Design

High-Performance Parallel Clustering

Member

Theory of Computation Community of Research

Systems Community of Research

Parallel computing, applied algorithms, graph processing.

PI
Core/Dual

Armando Solar-Lezama

Associate Professor

Programming languages, software analysis

E asolar@csail.mit.edu

T 258-9727

Lead

Computation Structures Group

Synquid: Synthesis From Liquid Types

Computer-Aided Programming

An Interlock for Self Driving Cars

Member

Center for Deployable Machine Learning (CDML)