Research

Impact Areas

Lead

Lalana Kagal

Tim Berners-Lee

Lalana Kagal

Tim Berners-Lee

Research Group

Sussman Lab

We focus on understanding the problem-solving strategies used by scientists and engineers, with the goals of automating parts of the process and formalizing educational methods.

Gerald Sussman

Leads

Gerald Sussman

Research Areas

Impact Areas

Lead

Gerald Sussman

Research Group

Lecturers

Lecturers in CSAIL

Leads

Research Areas

Impact Areas

Community of Research

Computing & Society Community of Research

This community is interested in understanding and affecting the interaction between computing systems and society through engineering, computer science and public policy research, education, and public engagement.

Daniel Weitzner

Leads

Daniel Weitzner

Research Areas

Impact Areas

Lead

Daniel Weitzner

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

Natural Language Processing Group

Impact Areas

Lead

Martin Rinard

5 Project Results matching all criteria

Project

Aspect-Augmented Adversarial Networks for Domain Adaptation

We propose a novel aspect-augmented adversarial network for cross-aspect and cross-domain adaptation tasks. The effectiveness of our approach suggests the potential application of adversarial networks to a broader range of NLP tasks for improved representation learning, such as machine translation and language generation.

Regina Barzilay

Tommi Jaakkola

Leads

Regina Barzilay

Tommi Jaakkola

Research Areas

Decentralized Information Group

Regina Barzilay

Tommi Jaakkola

Project

The Car Can Explain!

Developing techniques to allow self-driving cars and other AI-driven systems to explain behaviors and failures.

Gerald Sussman

Lalana Kagal

Leads

Gerald Sussman

Lalana Kagal

Research Areas

Impact Areas

Gerald Sussman

Lalana Kagal

Project

Better Models for Ride-Sharing

Traffic is not just a nuisance for drivers: It’s also a public health hazard and bad news for the economy.

Leads

Research Areas

Impact Areas

Energy

Project

EQ-Radio: Emotion Recognition using Wireless Signals

Networks at MIT

EQ-Radio can infer a person’s emotions using wireless signals. It transmits an RF signal and analyzes its reflections off a person’s body to recognize his emotional state (happy, sad, etc.).

Dina Katabi

Leads

Dina Katabi

Research Areas

Impact Areas

Entertainment

Computer-Aided Programming

Internet of Things

Dina Katabi

Project

An Interlock for Self Driving Cars

Software Design Group

Human-Computer Interaction Community of Research

Self-driving cars are likely to be safer, on average, than human-driven cars. But they may fail in new and catastrophic ways that a human driver could prevent. This project is designing a new architecture for a highly dependable self-driving car.

Daniel Jackson

Armando Solar-Lezama

Leads

Daniel Jackson

Armando Solar-Lezama

Research Areas

Impact Areas

Daniel Jackson

Armando Solar-Lezama

14 People Results matching all criteria

Anish Athalye

Graduate Student

PhD student in PDOS

E aathalye@mit.edu

RM 32-G978A

PhD student in PDOS

Laurent Bindschaedler

Postdoctoral Fellow

Systems for Big Data and ML. ML for Systems.

E bindscha@mit.edu

Member

Adversarial Cyber Security

Systems for Big Data and ML. ML for Systems.

Valentin Churavy

Graduate Student

#JuliaLang, #GPU, #HPC

E vchuravy@MIT.EDU

Member

Julia Lab

#JuliaLang, #GPU, #HPC

Gregory Falco

Research Affiliate

Dr. Falco is a hacker and expert in IoT and IIoT cybersecurity.

E gfalco@mit.edu

Dr. Falco is a hacker and expert in IoT and IIoT cybersecurity.

PI
Core/Dual

Lalana Kagal

Principal Research Scientist

Privacy, web decentralization, distributed data

E lkagal@csail.mit.edu

T 253-5845

Lead

Decentralized Information Group

The Car Can Explain!

Internet Policy Research Initiative

Solid: Social Linked Data

PrivacyML - A Privacy Preserving Framework for Machine Learning

Member

Privacy, web decentralization, distributed data

PI
Core/Dual

David Karger

Professor

Helping people manage information

E karger@csail.mit.edu

T 258-6167

Lead

Haystack Group

Mavo: Creating Interactive Data-Driven Web Applications by Authoring HTML

Algorithms Group

Wikum: Bridging Discussion Systems and Wikis with Collective Summarization

Squadbox: Combating Online Harassment using Friendsourced Moderation

Eyebrowse: Social and Public Web Browsing

Talkademic: Motivating Online Academic Discourse

Member

Human-Computer Interaction Community of Research

Theory of Computation Community of Research

EQ-Radio: Emotion Recognition using Wireless Signals

Helping people manage information

PI
Core/Dual

Dina Katabi

Professor

Wireless, networks, machine learning

E dina@csail.mit.edu

T 324-6027

Lead

Networks at MIT

Member

Wireless, networks, machine learning

PI
Core/Dual

Tim Kraska

Associate Professor

Systems for ML, ML for Systems, Interactive Data Exploration

E kraska@mit.edu

Lead

Member

Systems for ML, ML for Systems, Interactive Data Exploration

Ryan Marcus

Postdoctoral Associate

Machine learning for systems

E ryanmarcus@csail.mit.edu

Member

Machine learning for systems

William Moses

Graduate Student

E wmoses@mit.edu

Lead

Tapir

PI
Core/Dual

Daniela Rus

Director

CSAIL director, robotics, AI, data science, privacy

E rus@csail.mit.edu

T 258-7567

RM 32/ 32-368/ 374

Lead

Social Network Extraction from GPS Datasets with Coresets

Safety Standards for Autonomous Vehicles

Soft Contact Modeling

Practical Secure Computation

Self-Driving Vehicles

Robust Learning for Autonomous Vehicles

Brain-Controlled Robots

Planning in Congestion for Autonomous Vehicles

Socially-Compliant Behavior for Autonomous Driving

Coresets for Machine Learning Algorithms

M-Blocks Modular Robotics

Robot Compiler

Distributed Robot Garden

Route and Motion Planning for Mobility-on-Demand with Rules of the Road

Member

Social Network Extraction from GPS Datasets with Coresets

Task-Driven Co-Optimization Of Articulated Robots

Wearable Blind Navigation

Drones that Drive

Better Models for Ride-Sharing

SoFi - The Soft Robotic Fish

Controlling drones and other robots with gestures

Using Muscle Signals to Lift Objects with Robots

Embodied Intelligence Community of Research

Helping robots learn using demonstrations

CSAIL director, robotics, AI, data science, privacy

Ibrahim Sabek

Postdoctoral Associate

E ibrahimsabek@csail.mit.edu

Member

Computational Cognitive Science Group

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

Visual Computing Community of Research

Computational cognitive science, machine learning

PI
Core/Dual

Daniel Weitzner

Principal Research Scientist

Web policy, cybersecurity, web architecture

E djweitzner@csail.mit.edu

T 253-8036

Lead

Internet Policy Research Initiative

Keys Under Doormats

Member

Web policy, cybersecurity, web architecture

12 News Results matching all criteria

AI & ML Robotics Systems & Networking

March 23 '21

More transparency and understanding into machine behaviors

A new tool helps humans better understand and develop artificial intelligence models by searching and highlighting representative scenarios.

More transparency and understanding into machine behaviors

Algorithms & Theory AI & ML Systems & Networking Health Care

March 23 '21

System detects errors when medication is self-administered

Wireless sensing technology could help improve patients’ technique with inhalers and insulin pens.

System detects errors when medication is self-administered

AI & ML Security & Cryptography Systems & Networking Health Care

April 09 '20

Automated Covid-19 contact tracing - while preserving privacy

New system uses Bluetooth signals from your smartphone, with the goal of automating Covid-19 contact tracing while preserving privacy

Automated Covid-19 contact tracing - while preserving privacy

An MIT-invented algorithm automatically produces a “portamento” effect — a pitch sliding from one note to another — between any two audio signals in real time. The algorithm finds the optimal way to move pitches from one signal into another to produce a smooth transition between sounds (shown here).

AI & ML Graphics & Vision Systems & Networking Entertainment

September 27 '19

Using math to blend musical notes seamlessly

Algorithm enables one audio signal to glide into another, recreating the “portamento” effect of some musical instruments.

Using math to blend musical notes seamlessly

Algorithms & Theory AI & ML Graphics & Vision Programming Languages & Software Engineering Systems & Networking Entertainment Manufacturing

August 05 '19

Computer-aided knitting

New CSAIL research uses machine learning to customize clothing designs

Computer-aided knitting

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

AI & ML Graphics & Vision Systems & Networking Health Care Manufacturing

June 18 '19

Teaching artificial intelligence to connect senses like vision and touch

MIT CSAIL system can learn to see by touching and feel by seeing, suggesting future where robots can more easily grasp and recognize objects.

Teaching artificial intelligence to connect senses like vision and touch

AI & ML Systems & Networking Health Care Wireless

January 31 '18

Tracking patients’ progress with radio signals and machine learning

Novartis researchers leverage in-house startup initiative to begin digital technology research collaboration.

Tracking patients’ progress with radio signals and machine learning

AI & ML Systems & Networking Health Care

August 21 '17

Using machine learning to improve patient care

Doctors are often deluged by signals from charts, test results, and other metrics to keep track of. It can be difficult to integrate and monitor all of these data for multiple patients while making real-time treatment decisions, especially when data is documented inconsistently across hospitals. In a new pair of papers, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) explore ways for computers to help doctors make better medical decisions.

Using machine learning to improve patient care

Humans and machines were given an image of a novel character (top) and asked to produce new versions. A machine generated the nine-character grid on the left.

AI & ML Graphics & Vision Systems & Networking

December 10 '15

Computer drawings fool human judges, pass “visual Turing test”

Researchers at CSAIL, New York University, and the University of Toronto have developed a computer system whose ability to produce a variation of a character in an unfamiliar writing system, on the first try, is indistinguishable from that of humans. That means that the system in some sense discerns what’s essential to the character — its general structure — but also what’s inessential — the minor variations characteristic of any one instance of it.

Computer drawings fool human judges, pass “visual Turing test”

How artificial intelligence can be used to sift through thousands of pages of tax law to root out shady tax-shelters.

AI & ML Security & Cryptography Systems & Networking Big Data Cybersecurity

October 17 '15

Tax-evading corporations, watch out: our AI knows what you're doing

CSAIL researchers recently helped develop "STEALTH," a system that uses artificial intelligence to combat tax evasion by corporations.

Tax-evading corporations, watch out: our AI knows what you're doing

Algorithms & Theory AI & ML Systems & Networking Big Data Energy

July 17 '15

What better wind-speed prediction can do for the energy industry

When a power company wants to build a new wind farm, it generally hires a consultant to make wind speed measurements at the proposed site for eight to 12 months. Those measurements are correlated with historical data and used to assess the site’s power-generation capacity.This month CSAIL researchers will present a new statistical technique that yields better wind-speed predictions than existing techniques do — even when it uses only three months’ worth of data. That could save power companies time and money, particularly in the evaluation of sites for offshore wind farms, where maintaining measurement stations is particularly costly.

What better wind-speed prediction can do for the energy industry

46 Group Results

Research Group

Advanced Network Architecture Group

The challenge that motivates the ANA group is to foster a healthy future for the Internet. The interplay of private sector investment, public sector regulation and public interest advocacy, as well as the global diversity in drivers and aspirations, makes for an uncertain future.

David Clark

Karen Sollins

Leads

David Clark

Karen Sollins

Research Areas

Impact Areas

Wireless

Lead

David Clark

Karen Sollins

David Clark

Karen Sollins

Research Group

Anyscale Learning for All ALFA

Our vision is data-driven machine learning systems that advance the quality of healthcare, the understanding of cyber arms races and the delivery of online education.

Una-May O'Reilly

Leads

Una-May O'Reilly

Research Areas

Impact Areas

Lead

Una-May O'Reilly

Community of Research

Applied Machine Learning Community of Research

This CoR brings together researchers at CSAIL working across a broad swath of application domains. Within these lie novel and challenging machine learning problems serving science, social science and computer science.

Una-May O'Reilly

Leads

Una-May O'Reilly

Research Areas

Impact Areas

Lead

Una-May O'Reilly

Research Group

Broderick Lab

We work in the areas of statistics and machine learning.

Tamara Broderick

Leads

Tamara Broderick

Research Areas

Impact Areas

Lead

Tamara Broderick

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

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

Lead

Peter Szolovits

+10

Peter Szolovits

Research Group

Clinical Machine Learning Group

Our group is interested in using machine learning and artificial intelligence to transform health care.

David Sontag

Leads

David Sontag

Research Areas

Impact Areas

Lead

David Sontag

Community of Research

Cognitive AI Community of Research

This CoR aims to develop AI technology that synthesizes symbolic reasoning, probabilistic reasoning for dealing with uncertainty in the world, and statistical methods for extracting and exploiting regularities in the world, into an integrated picture of intelligence that is informed by computational insights and by cognitive science.

Howard Shrobe

Leads

Howard Shrobe

Research Areas

Impact Areas

Lead

Howard Shrobe

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

Computer Architecture

Impact Areas

Wireless

Lead

Srini Devadas

Daniel Sanchez

Armando Solar-Lezama

Arvind

+21

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 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

Community of Research

Computing & Society Community of Research

Daniel Weitzner

Leads

Daniel Weitzner

Research Areas

Impact Areas

Lead

Daniel Weitzner

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

Wireless

Lead

Sam Madden

Michael Stonebraker

Tim Kraska

+15

Research Group

Data-Driven Inference Group

We use machine learning and computer vision to improve outcomes in medicine, finance, and sports

John Guttag

Leads

John Guttag

Research Areas

Impact Areas

Lead

John Guttag

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

Distributed Robotics Laboratory

We aim to develop the science of autonomy toward a future with robots and AI systems integrated into everyday life, supporting people with cognitive and physical tasks.

+11

Daniela Rus

Leads

Daniela Rus

Research Areas

Impact Areas

Lead

Daniela Rus

+11

Daniela Rus

Research Group

Genesis Group

The Genesis Group focuses on developing an account of human intelligence with special
emphasis on developing computational models of how people tell, perceive and understand
stories.

Leads

Research Areas

Impact Areas

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

Imagination, Computation, and Expression Laboratory (ICE Lab)

We develop computing systems for creative expression, cultural analysis, and social change.

Peter Mawhorter

D. Fox Harrell

Leads

D. Fox Harrell

Research Areas

Impact Areas

Entertainment

Lead

D. Fox Harrell

Peter Mawhorter

D. Fox Harrell

Research Group

Infolab

We investigate language in different contexts: from how it is learned, to how it is grounded in visual perception, all the way to how machines can readily interact with humans.

Boris Katz

Leads

Boris Katz

Research Areas

Impact Areas

Lead

Boris Katz

Research Center

Internet Policy Research Initiative

Our mission is to work with policy makers and cybersecurity technologists to increase the trustworthiness and effectiveness of interconnected digital systems.

Leads

Daniel Weitzner

Hal Abelson

David Clark

Lalana Kagal

Karen Sollins

Gerald Sussman

Research Areas

Impact Areas

Lead

Daniel Weitzner

Hal Abelson

David Clark

Lalana Kagal

Karen Sollins

Gerald Sussman

Research Group

Learning and Intelligent Systems

We conduct interdisciplinary research aimed at discovering the principles underlying the design of artificially intelligent robots.

Leslie Kaelbling

Tomas Lozano-Perez

Leads

Leslie Kaelbling

Tomas Lozano-Perez

Research Areas

Impact Areas

Lead

Leslie Kaelbling

Tomas Lozano-Perez

Leslie Kaelbling

Tomas Lozano-Perez

109 Project Results

Project

3D Generative Adversarial Networks

Vision Group

We study the problem of 3D object generation. We propose a novel framework, 3D Generative Adversarial Network (3D-GAN), leveraging recent advances in volumetric convolutional networks and generative adversarial nets.

Leads

Research Areas

Impact Areas

Computation Structures Group

Project

[Inactive] T-1000: A Thousand-Core Coherent Shared Memory System

(This project is no longer active.) The T-1000, a prototype system of a thousand realistic processors embedded throughout an ensemble of interconnected FPGAs, seeks to demonstrate the scalability of timestamp-based cache coherence protocols on distributed shared memory systems.

Quan Nguyen

Leads

Quan Nguyen

Research Areas

Computer Architecture

Learning and Intelligent Systems

Quan Nguyen

Project

Active Learning of Models for Planning

We aim to develop a systematic framework for robots to build models of the world and to use these to make effective and safe choices of actions to take in complex scenarios.

Leslie Kaelbling

Tomas Lozano-Perez

Leads

Leslie Kaelbling

Tomas Lozano-Perez

Research Areas

Impact Areas

Entertainment

Leslie Kaelbling

Tomas Lozano-Perez

Project

AdaptDB: Adaptive Partitioning for Distributed Joins

Our goal is to develop an adaptive storage manager for analytical database workloads in a distributed setting. It works by partitioning datasets across a cluster and incrementally refining data partitioning as queries are run.

Leads

Research Areas

Impact Areas

Anyscale Learning for All ALFA

Project

Adversarial Cyber Security

Applied Machine Learning Community of Research

Our goal is to understand the nature of cyber security arms races between malicious and bonafide parties. Our vision is autonomous cyber defenses that anticipate and take measures against counter attacks.

Una-May O'Reilly

Leads

Una-May O'Reilly

Research Areas

Impact Areas

Networks and Mobile Systems

Una-May O'Reilly

Project

Aggregate Congestion Control

Develop a method for sending persistently backlogged traffic on the Internet while adapting to link conditions dynamically.

Akshay Narayan

Francis Cangialosi

Leads

Akshay Narayan

Francis Cangialosi

Research Areas

Impact Areas

Akshay Narayan

Francis Cangialosi

Project

Amoeba: A shape changing storage system for big data

Amoeba is a distributed storage system that efficiently supports ad-hoc and exploratory analytics using adaptive data partitioning

Alekh Jindal

Leads

Research Areas

Computer-Aided Programming

Alekh Jindal

Project

An Interlock for Self Driving Cars

Software Design Group

Human-Computer Interaction Community of Research

Daniel Jackson

Armando Solar-Lezama

Leads

Daniel Jackson

Armando Solar-Lezama

Research Areas

Impact Areas

Interactive Robotics Group

Daniel Jackson

Armando Solar-Lezama

Project

Apprenticeship Scheduling: Learning to Schedule From Human Experts

Robot scheduling via learning from demonstration for tasks in medicine and more

Leads

Research Areas

Impact Areas

Project

Approximate String Joins with Abbreviations

We propose efficient and effective algorithms to perform approximate string joins with abbreviations in database systems.

Wenbo Tao

Leads

Wenbo Tao

Research Areas

Spoken Language Systems Group

Wenbo Tao

Project

Arabic Language Processing

The Arabic language is spoken by over one billion people around the world. Arabic presents a variety of challenges for speech and language processing technologies. In our group, we have several research topics examining Arabic, including dialect identification, speech recognition, machine translation, and language processing.

Mitra Mohtarami

Leads

Mitra Mohtarami

Research Areas

Weiss Laboratory for Synthetic Biology

Mitra Mohtarami

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

Natural Language Processing Group

Project

Aspect-Augmented Adversarial Networks for Domain Adaptation

Regina Barzilay

Tommi Jaakkola

Leads

Regina Barzilay

Tommi Jaakkola

Research Areas

Regina Barzilay

Tommi Jaakkola

Project

Aurum: Large Scale Data Discovery

Aurum is a data discovery system that works at large scale, helping people find relevant data.

Sam Madden

Michael Stonebraker

Leads

Sam Madden

Michael Stonebraker

Research Areas

Impact Areas

Spoken Language Systems Group

Sam Madden

Michael Stonebraker

Project

Automatic Speech Recognition

Automatic speech recognition (ASR) has been a grand challenge machine learning problem for decades. Our ongoing research in this area examines the use of deep learning models for distant and noisy recording conditions, multilingual, and low-resource scenarios.

Sameer Khurana

Jim Glass

Leads

Sameer Khurana

Jim Glass

Research Areas

Impact Areas

Sameer Khurana

Jim Glass

Project

Autonomous Vehicle Databases

The impending success of AV technology will create vehicles that collect sensor data at a high rate.

Michael Stonebraker

Sam Madden

Leads

Michael Stonebraker

Sam Madden

Research Areas

Impact Areas

Clinical Decision-Making Group

Michael Stonebraker

Sam Madden

Project

AWE-CM Vectors: Augmenting Word Embeddings with a Clinical Metathesaurus

Applied Machine Learning Community of Research

Adding domain knowledge to word embeddings.

Peter Szolovits

Leads

Peter Szolovits

Research Areas

Impact Areas

Peter Szolovits

Project

Bayesian Optimization for Global Optimization of Expensive Black-box Functions

Learning and Intelligent Systems

We study the fundamentals of Bayesian optimization and develop efficient Bayesian optimization methods for global optimization of expensive black-box functions originated from a range of different applications.

Leads

Research Areas

Impact Areas

Project

Better Models for Ride-Sharing

Traffic is not just a nuisance for drivers: It’s also a public health hazard and bad news for the economy.

Leads

Research Areas

Impact Areas

Energy

Computation Structures Group

Project

BlueDBM: Distributed Flash Storage for Big Data Analytics

BlueDBM is an architecture of computer clusters consisting of fast distributed flash storage and in-storage accelerators, which often outperforms larger and more expensive clusters in applications such as graph analytics.

Leads

Research Areas

Computer Architecture

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

Building a Scalable Database for Autonomous Vehicles

We are building a database for autonomous vehicle sensor data that addresses the challenges presented by the potential scale of autonomous vehicle data and the unique characteristics of the data.

Leads

Michael Stonebraker

Sam Madden

Oscar Ricardo Moll Thomae

Research Areas

Decentralized Information Group

Project

The Car Can Explain!

Developing techniques to allow self-driving cars and other AI-driven systems to explain behaviors and failures.

Gerald Sussman

Lalana Kagal

Leads

Gerald Sussman

Lalana Kagal

Research Areas

Impact Areas

Gerald Sussman

Lalana Kagal

Project

Cardiac MRI analysis

Medical Vision Group

Vision Group

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

Embodied Intelligence Community of Research

Polina Golland

130 People Results

PI
Core/Dual

Ted Adelson

Professor

Vision, touch sensing, robotics

E adelson@csail.mit.edu

T 253-0645

Lead

Vision Group

Blood Pressure Imager

Member

Visual Computing Community of Research

Vision, touch sensing, robotics

Monica Agrawal

Graduate Student

E magrawal@mit.edu

Leandro Agudelo

Research Scientist

Systems Genomics, CompBio, Topological Integrative Biology, Biology

E lagudelo@csail.mit.edu

Systems Genomics, CompBio, Topological Integrative Biology, Biology

Ekin Akyürek

Graduate Student

First year PhD student in computer science

E akyurek@mit.edu

First year PhD student in computer science

Alexander Amini

Graduate Student

PhD Candidate. Deep Learning; Robotics

E Amini@mit.edu

Lead

Robust Learning for Autonomous Vehicles

Member

Self-Driving Vehicles

Natural Language Processing Group

PhD Candidate. Deep Learning; Robotics

Brandon Araki

Graduate Student

E araki@csail.mit.edu

Venkat Arun

Graduate Student

Congestion control, applied cryptography

E venkatar@MIT.EDU

Congestion control, applied cryptography

Anish Athalye

Graduate Student

PhD student in PDOS

E aathalye@mit.edu

RM 32-G978A

PhD student in PDOS

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

Applied Machine Learning Community of Research

Natural language processing, machine learning

Cenk Baykal

Graduate Student

E baykal@mit.edu

RM 32-376C

Member

Coresets for Machine Learning Algorithms

Jonathan Behrens

Graduate Student

E behrensj@mit.edu

RM 32-G978B

Member

Noria: a new data-flow system for web applications

Parallel and Distributed Operating Systems

PI
Core/Dual

Adam Belay

Assistant Professor

Operating systems, networking, systems security, and performance

E abelay@CSAIL.MIT.EDU

T 253-0004

Lead

Parallel and Distributed Operating Systems

Member

Operating systems, networking, systems security, and performance

Laurent Bindschaedler

Postdoctoral Fellow

Systems for Big Data and ML. ML for Systems.

E bindscha@mit.edu

Member

Synthetically-Identified Clinical Notes

Systems for Big Data and ML. ML for Systems.

William Boag

Graduate Student

Clinical NLP

E wboag@mit.edu

Lead

Information Retrieval for Cancer Treatments in Clinical Literature and Trial Eligibility

CliNER: Clinical Concept Extraction

Quantifying Racial Disparities in End-of-Life Care

Member

Clinical Decision-Making Group

Clinical NLP

Laura E. Brandt

Graduate Student

E lebrandt@csail.mit.edu

PI
Core/Dual

Tamara Broderick

Associate Professor

Machine learning, statistics, Bayesian methods, inference

E tbroderick@csail.mit.edu

T 324-6749

Lead

Scalable Bayesian Inference via Adaptive Data Summaries

Scalable Bayesian inference with optimization

Broderick Lab

Member

Machine learning, statistics, Bayesian methods, inference

Noam Buckman

Graduate Student

PhD Candidate. Autonomous vehicles. Multi-robot systems.

E nbuckman@mit.edu

Member

Model-Based Embedded and Robotics Systems Group

Self-Driving Vehicles

PhD Candidate. Autonomous vehicles. Multi-robot systems.

Richard Camilli

Research Affiliate

E romeo@mit.edu

Member

Tej Chajed

Graduate Student

PhD student in systems

E tchajed@csail.mit.edu

RM 32-G978B

Lead

FSCQ: File-system verification

Perennial

Member

Parallel and Distributed Operating Systems

PhD student in systems

Geeticka Chauhan

Graduate Student

E geeticka@mit.edu

Member

Clinical Decision-Making Group

Quantification of Pulmonary Edema in Chest Radiographs

Irene Chen

Graduate Student

Machine learning, healthcare, fairness

E iychen@mit.edu

Member

Clinical Machine Learning Group

Kami: A Modular Deductive Hardware Verification Platform

Machine learning, healthcare, fairness

PI
Core/Dual

Adam Chlipala

Associate Professor

Programming languages, formal methods, security & privacy, systems

E adamc@csail.mit.edu

T 324-8439

Lead

Compilation Using Correct-by-Construction Program Synthesis

Programming Languages & Verification

Hemiola: Structural Design and Proof of Cache-Coherence Protocols

High-Assurance Software

High-Assurance Hardware

High-Assurance Cryptography

Member

Compilation Using Correct-by-Construction Program Synthesis

Programming with spaces

Computation Structures Group

FSCQ: File-system verification