Research

Decentralized Information Group

Impact Areas

Lead

Daniela Rus

+15

Daniela Rus

1 Project Results matching all criteria

Project

PrivacyML - A Privacy Preserving Framework for Machine Learning

We are developing a general framework that enforces privacy transparently enabling different kinds of machine learning to be developed that are automatically privacy preserving.

Lalana Kagal

Vaikkunth Mugunthan

Leads

Lalana Kagal

Vaikkunth Mugunthan

Research Areas

Noria: a new data-flow system for web applications

Impact Areas

Lalana Kagal

Vaikkunth Mugunthan

3 People Results matching all criteria

Jonathan Behrens

Graduate Student

E behrensj@mit.edu

RM 32-G978B

Member

Parallel and Distributed Operating Systems

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

CSAIL director, robotics, AI, data science, privacy

Yu Wang

Graduate Student

E wangyu9@mit.edu

RM 32-D475A

Lead

Boundary Element Method for Shape Analysis and Geometry Processing

Member

Geometric Data Processing Group

2 News Results matching all criteria

Algorithms & Theory Computer Architecture Big Data Cybersecurity Health Care Internet of Things Manufacturing

January 31 '19

MIT hosts workshop on theoretical foundations of deep learning

Last week MIT’s Institute for Foundations of Data Science (MIFODS) held an interdisciplinary workshop aimed at tackling the underlying theory behind deep learning. Led by MIT professor Aleksander Madry, the event focused on a number of research discussions at the intersection of math, statistics, and theoretical computer science.

MIT hosts workshop on theoretical foundations of deep learning

Algorithms & Theory Security & Cryptography Big Data Cybersecurity Education Entertainment Health Care Internet of Things Manufacturing

January 16 '18

Goldwasser, Micali, and Rivest win BBVA Foundation Frontiers of Knowledge Awards

This week it was announced that MIT professors and CSAIL principal investigators Shafi Goldwasser, Silvio Micali, Ronald Rivest, and former MIT professor Adi Shamir won this year’s BBVA Foundation Frontiers of Knowledge Awards in the Information and Communication Technologies category for their work in cryptography.

Goldwasser, Micali, and Rivest win BBVA Foundation Frontiers of Knowledge Awards

44 Group Results

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

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 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

Cybersecurity

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

Research Group

Complexity Theory Group

Our interests span quantum complexity theory, barriers to solving P versus NP, theoretical computer science with a focus on probabilistically checkable proofs (PCP), pseudo-randomness, coding theory, and algorithms.

Leads

Shafi Goldwasser

Ronitt Rubinfeld

Michael Sipser

Ryan Williams

Virginia Vassilevska Williams

Research Areas

Impact Areas

Cybersecurity

Lead

Shafi Goldwasser

Ronitt Rubinfeld

Michael Sipser

Ryan Williams

Virginia Vassilevska Williams

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 Fabrication Group

Our research centers on digital manufacturing, 3D printing and computer graphics, as well as computational photography and displays, and virtual humans and robotics.

Wojciech Matusik

Leads

Wojciech Matusik

Research Areas

Impact Areas

Lead

Wojciech Matusik

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

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.

+15

Daniela Rus

Leads

Daniela Rus

Research Areas

Impact Areas

Lead

Daniela Rus

+15

Daniela Rus

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

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

HCI Engineering Group

We work at the intersection of human computer interaction and personal fabrication tools.

Stefanie Mueller

Leads

Stefanie Mueller

Research Areas

Impact Areas

Lead

Stefanie Mueller

Research Group

Imagination, Computation, and Expression Laboratory (ICE Lab)

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

Peter Mawhorter

James Bowie Wilson

D. Fox Harrell

Leads

D. Fox Harrell

Research Areas

Impact Areas

Entertainment

Lead

D. Fox Harrell

Peter Mawhorter

James Bowie Wilson

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 Group

Interactive Robotics Group

The Interactive Robotics Group aims to imagine the future of work by designing collaborative robot teammates that enhance human capability.

Julie Shah

Leads

Julie Shah

Research Areas

Impact Areas

Transportation

Lead

Julie Shah

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

93 Project Results

Project

3D Generative Adversarial Networks

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

Computational Fabrication Group

Project

3D-Printed Organic Solar Cells

Using our inkjet printer system, the goal of this project is to produce a light sensor / solar cell that is composed entirely of 3D printed materials.

James Minor

Leads

James Minor

Research Areas

Impact Areas

Computational Cognitive Science Group

James Minor

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

Learning and Intelligent Systems

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.

Leads

Zi Wang

Leslie Kaelbling

Tomas Lozano-Perez

Research Areas

Impact Areas

Entertainment

Project

AdaptDB: Adaptive Partitioning for Distributed Joins

Data Systems Group

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.

Yi Lu

Leads

Yi Lu

Research Areas

Impact Areas

Theory of Computation Group

Yi Lu

Project

Algorithmic Aspects of Performance Engineering

Supertech Research Group

The project concerns algorithmic solutions for writing fast codes.

Leads

Research Areas

Impact Areas

Wireless

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. Now one of the main challenges is to make the system more usable and understandable for the user.

Daniel Jackson

Leads

Daniel Jackson

Research Areas

Interactive Robotics Group

Impact Areas

Daniel Jackson

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

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

Aurum: Large Scale Data Discovery

Data Systems Group

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

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.

Leads

Hao Tang

Wei-Ning Hsu

David Harwath

Sameer Khurana

Di-Chia Chueh

Jim Glass

Research Areas

Impact Areas

Project

Autonomous Vehicle Databases

Data Systems Group

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

Transportation

Michael Stonebraker

Sam Madden

Project

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

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.

Zi Wang

Leads

Zi Wang

Research Areas

Impact Areas

Zi Wang

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

Computation Structures Group

Energy

Transportation

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

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

Chest X-Ray Analysis

We develop machine learning algorithms to automatically quantify the severity of pulmonary edema from chest x-rays.

Polina Golland

Leads

Polina Golland

Research Areas

Impact Areas

Polina Golland

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

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

Polina Golland

Project

Clinical Note Representations That Predict ICU Mortality/Re-Admission

Our focus is on improving health-related outcomes by creating machine learning models that improve human risks.

Peter Szolovits

Leads

Peter Szolovits

Research Areas

Impact Areas

Peter Szolovits

Project

Community Question Answering

Our main goal is to automatically search for relevant answers among many responses provided for a given question (Answer Selection), and search for relevant questions to reuse their existing answers (Question Retrieval).

Mitra Mohtarami

Leads

Mitra Mohtarami

Research Areas

Impact Areas

Mitra Mohtarami

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.

Julian Shun

Leads

Julian Shun

Research Areas

Impact Areas

Julian Shun

109 People Results

Mazdak Abulnaga

Graduate Student

medical vision

E abulnaga@mit.edu

Member

Monitoring Fetal Health

medical vision

PI
Core/Dual

Ted Adelson

Professor

Vision, touch sensing, robotics

E adelson@csail.mit.edu

T 253-0645

Lead

Simit: A Language for Computing on Sparse Systems

Blood Pressure Imager

Member

Computer Graphics Group

Vision, touch sensing, robotics

Monica Agrawal

Graduate Student

E magrawal@mit.edu

Leandro Agudelo

Postdoctoral Associate

Computational Biology, Integrative Systems Biology

E lagudelo@csail.mit.edu

Computational Biology, Integrative Systems Biology

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

Compilers, architectures, software engineering

Alexander Amini

Graduate Student

PhD Candidate. Deep Learning; Robotics

E Amini@mit.edu

Lead

Robust Learning for Autonomous Vehicles

Member

Self-Driving Vehicles

Fact-Checking and Reasoning

PhD Candidate. Deep Learning; Robotics

Mercy Asiedu

Postdoctoral Fellow

E mnasiedu@csail.mit.edu

Ramy Baly

Postdoctoral Associate

E baly@mit.edu

Lead

Arabic Language Processing

Member

Natural Language Processing Group

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

Aspect-Augmented Adversarial Networks for Domain Adaptation

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

Bonnie Berger

Professor

Computational biology, genomics

E bab@csail.mit.edu

T 253-1827

Lead

Theory of Computation Group

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

Computational biology, genomics

PI
Core/Dual

Tim Berners-Lee

Professor

Systems, privacy, inventor of the World Wide Web

E timbl@w3.org

T 253-5702

Lead

Decentralized Information Group

World Wide Web Consortium

Solid: Social Linked Data

Systems, privacy, inventor of the World Wide Web

William Boag

Graduate Student

Clinical NLP

E wboag@mit.edu

Lead

Synthetically-Identified Clinical Notes

Information Retrieval for Cancer Treatments in Clinical Literature and Trial Eligibility

CliNER: Clinical Concept Extraction

Quantifying Racial Disparities in End-of-Life Care

Member

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

Clinical NLP

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

Machine learning, statistics, Bayesian methods, inference

Richard Camilli

Research Affiliate

E romeo@mit.edu

Member

Model-Based Embedded and Robotics Systems Group

PI
Core/Dual

Michael Carbin

Assistant Professor

Programming languages and systems.

E mcarbin@csail.mit.edu

T 253-5881

Lead

Programming Systems Group

Member

Programming with spaces

Program Performance Prediction with Deep Learning

Programming languages and systems.

Geeticka Chauhan

Graduate Student

E geeticka@mit.edu

Member

Using Clinical Domain Knowledge for Processing Physiological Data

Clinical Machine Learning Group

Irene Chen

Graduate Student

Machine learning, healthcare, fairness

E iychen@mit.edu

Member

Sensorized Soft Electric Hands with Handed Shearing Auxetics

Machine learning, healthcare, fairness

Lillian Chin

Graduate Student

E ltchin@mit.edu

Lead

Member

Unsupervised Speech Processing

Yu-An Chung

Graduate Student

Speech and language processing, machine learning

E andyyuan@mit.edu

Lead

Member

Speech and language processing, machine learning

Adrian Dalca

Research Affiliate

E adalca@csail.mit.edu

Member

Theory of Computation Group

Clinical Neuroimaging

PI
Core/Dual

Costis Daskalakis

Associate Professor

Theory, algorithms, economics, game theory

E costis@csail.mit.edu

T 253-9643

Lead

Is the Casino using a Riffle Shuffle?

Understanding Convergence of Iterative Algorithms

Theory, algorithms, economics, game theory

PI
Core/Dual

Randall Davis

Professor

Human-computer interaction, systems, classic AI

E davis@csail.mit.edu

T 253-5879

Lead