Research

Impact Areas

Lead

Justin Solomon

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

14 Project Results matching all criteria

Project

Distributed Computation in Ant Colonies

We are interested in applying insights from distributed computing theory to understand how ants and other social insects work together to perform complex tasks such as foraging for food, allocating tasks to workers, and choosing high quality nest sites.

Nancy Lynch

Leads

Nancy Lynch

Research Areas

Nancy Lynch

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

Computational Biology

Impact Areas

Yaron Meirovitch

Nir Shavit

Project

Safety Standards for Autonomous Vehicles

In this project, we aim to develop a framework that can ensure and certify the safety of an autonomous vehicle. By leveraging research from the area of formal verification, this framework aims to assess the safety, i.e., free of collisions, of a broad class of autonomous car controllers/planners for a given traffic model.

Leads

Lucas Liebenwein

Wilko Schwarting

Daniela Rus

Research Areas

Impact Areas

Transportation

Project

Driver-Friendly Bilateral Control for Suppressing Traffic Instabilities

Vision Group

Self-driving cars themselves can solve traffic problems even without global control.

Leads

Research Areas

Project

Practical Secure Computation

Our goal is to bridge theory and practice to create infrastructure that allow computation and multi-party computation without compromising privacy.

Daniela Rus

Danny Feldman

Leads

Daniela Rus

Danny Feldman

Research Areas

Daniela Rus

Danny Feldman

Project

Reliable and Robust Machine Learning

We work towards a principled understanding of the current machine learning toolkit and making this toolkit be robust and reliable.

Aleksander Madry

Leads

Aleksander Madry

Research Areas

Impact Areas

Aleksander Madry

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

Sublinear/Streaming Algorithms for Covering Problem

Our goal is to develop efficient algorithms for the fundamental set cover problem in the massive data model.

Piotr Indyk

Ronitt Rubinfeld

Leads

Piotr Indyk

Ronitt Rubinfeld

Research Areas

Piotr Indyk

Ronitt Rubinfeld

Project

Return of the Byzantine Generals

This project studies new solutions to the Byzantine General Problem and its applications in distributed systems and cryptography.

Srini Devadas

Leads

Srini Devadas

Research Areas

Srini Devadas

Project

Understanding Convergence of Iterative Algorithms

We are trying to develop theoretical tools that can be used to analyze the convergence of iterative algorithms used for non-convex optimization problems.

Costis Daskalakis

Leads

Costis Daskalakis

Research Areas

Costis Daskalakis

Project

Is the Casino using a Riffle Shuffle?

Our goal in this project is to understand how one can test if a particular dealer's shuffles follow a certain pattern. We have developed a theoretical framework for the same and wish to understand its performance in practice.

Costis Daskalakis

Nick Gravin

Leads

Costis Daskalakis

Nick Gravin

Research Areas

Costis Daskalakis

Nick Gravin

Project

A Simplified and Extensible Cilk Runtime for Research

CilkS is a new runtime system for the Cilk multithreaded programming environment which makes it easy to experiment with new algorithms, data structures, and programming linguistics.

Charles E. Leiserson

Tao Schardl

Leads

Charles E. Leiserson

Tao Schardl

Research Areas

Charles E. Leiserson

Tao Schardl

Project

Optimal transport for statistics and machine learning

Linking probability with geometry to improve the theory and practice of machine learning

Justin Solomon

Leads

Justin Solomon

Research Areas

Impact Areas

Justin Solomon

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

40 People Results matching all criteria

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

Applied Machine Learning Community of Research

Natural language processing, machine learning

Cenk Baykal

Graduate Student

E baykal@mit.edu

RM 32-376C

Member

PI
Core/Dual

Costis Daskalakis

Associate Professor

Algorithms, Economics, Game Theory, Statistics, Machine Learning

E costis@csail.mit.edu

T 253-9643

Lead

Is the Casino using a Riffle Shuffle?

Understanding Convergence of Iterative Algorithms

Member

Algorithms, Economics, Game Theory, Statistics, Machine Learning

PI
Core/Dual

Erik Demaine

Professor

Algorithms, theory, computational geometry, complexity

E edemaine@mit.edu

T 253-6871

Lead

Member

Algorithms, theory, computational geometry, complexity

Martin Demaine

Robotics Engineer

E mdemaine@mit.edu

T 253-7953

Barış Ekim

Graduate Student

E ekim@csail.mit.edu

PI
Core/Dual

Shafi Goldwasser

Professor

Theory, cryptography, cybersecurity, complexity

E shafi@csail.mit.edu

T 253-5914

Lead

Complexity Theory Group

Member

Theory, cryptography, cybersecurity, complexity

Noah Golowich

Graduate Student

E nzg@mit.edu

RM 32-G585B

Joanne Hanley

Administrative Assistant II

Administrative Assistant, Theory of Computation

E joanne@csail.mit.edu

T 253-6054

Member

Administrative Assistant, Theory of Computation

Dhiraj Holden

Graduate Student

E dholden@mit.edu

PI
Core/Dual

Piotr Indyk

Professor

Algorithms, theory, computational geometry

E indyk@csail.mit.edu

T 452-3402

Lead

Sublinear/Streaming Algorithms for Covering Problem

Sublinear Algorithms for Massive Data Problems

Member

Algorithms, theory, computational geometry

PI
Core/Dual

Tommi Jaakkola

Professor

Machine learning, natural language processing, genomics

E tommi@csail.mit.edu

T 253-0440

Lead

Aspect-Augmented Adversarial Networks for Domain Adaptation

Learning Strategic Games

Structured Prediction Through Randomization

Interpretability in complex machine learning models

Member

Learning Optimal Interventions

Machine learning, natural language processing, genomics

Siddhartha Jayanti

Graduate Student

E siddhartha@csail.mit.edu

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

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

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

William Kuszmaul

Graduate Student

Research interests in algorithms and high-performance engineering

E kuszmaul@mit.edu

Research interests in algorithms and high-performance engineering

PI
Core/Dual

Charles E. Leiserson

Professor

Algorithms, parallel computing, performance engineering

E cel@csail.mit.edu

T 253-5833

Lead

Supertech Research Group

Performance Engineering of Cache Profilers

CilkPride

A Simplified and Extensible Cilk Runtime for Research

Determining Wikipedia's Influence on Science

Tapir

Member

Safety Standards for Autonomous Vehicles

Algorithms, parallel computing, performance engineering

Lucas Liebenwein

Graduate Student

Student and Researcher | Robotics, AI | Advanced Autonomy

E lucasl@mit.edu

RM 32-376C

Lead

Member

Self-Driving Vehicles

Student and Researcher | Robotics, AI | Advanced Autonomy

PI
Core/Dual

Aleksander Madry

Associate Professor

Theory, algorithms, optimization, robust and reliable ML

E madry@mit.edu

T 324-6739

Lead

Reliable and Robust Machine Learning

Member

Theory, algorithms, optimization, robust and reliable ML

PI
Core/Dual

Albert R. Meyer

Professor Emeritus

Programming languages, theory, complexity, online education

E meyer@csail.mit.edu

T 253-6024

Programming languages, theory, complexity, online education

Slobodan Mitrovic

Postdoctoral Associate

E slobo@mit.edu

PI
Core/Dual

Ankur Moitra

Associate Professor

Theory, algorithms, machine learning, complexity

E moitra@csail.mit.edu

T 253-5876

Lead

Efficient Robust Estimation in High Dimensions

Member

Theory, algorithms, machine learning, complexity

PI
Core/Dual

Ronald Rivest

Institute Professor

Cryptography, cybersecurity, RSA public-key encryption

E rivest@mit.edu

T 253-5880

Lead

Member

Computing & Society Community of Research

Cryptography, cybersecurity, RSA public-key encryption

81 News Results matching all criteria

Algorithms & Theory AI & ML

December 07 '20

Building machines that better understand human goals

A new algorithm capable of inferring goals and plans could help machines better adapt to the imperfect nature of human planning

Building machines that better understand human goals

Algorithms & Theory AI & ML

December 02 '20

Shrinking massive neural networks used to model language

A new approach could lower computing costs and increase accessibility to state-of-the-art natural language processing.

Shrinking massive neural networks used to model language

Algorithms & Theory Robotics

November 30 '20

Computer-aided creativity in robot design

MIT researchers’ new system optimizes the shape of robots for traversing various terrain types.

Computer-aided creativity in robot design

Algorithms & Theory AI & ML Computational Biology Health Care

November 04 '20

Algorithm reduces unnecessary use of antibiotics for UTIs

Machine learning model predicts probability that a patient’s UTI can be treated by various antibiotics

Algorithm reduces unnecessary use of antibiotics for UTIs

Algorithms & Theory Robotics Transportation

October 26 '20

Autonomous boats could be your next ride

Five years in the making, MIT’s autonomous floating vessels get a size upgrade and learn a new way to communicate aboard the waters.

Autonomous boats could be your next ride

Algorithms & Theory AI & ML Health Care

September 17 '20

Monitoring sleep positions for a healthy rest

Wireless device captures sleep data without using cameras or body sensors; could aid patients with Parkinson’s disease, epilepsy, or bedsores.

Monitoring sleep positions for a healthy rest

Algorithms & Theory AI & ML Programming Languages & Software Engineering

September 08 '20

Toward a machine learning model that can reason about everyday actions

Researchers train a model to reach human-level performance at recognizing abstract concepts in video.

Toward a machine learning model that can reason about everyday actions

Algorithms & Theory Programming Languages & Software Engineering Energy

August 12 '20

Shrinking deep learning’s carbon footprint

Through innovation in software and hardware, researchers move to reduce the financial and environmental costs of modern artificial intelligence.

Shrinking deep learning’s carbon footprint

Algorithms & Theory Systems & Networking

July 29 '20

Looking into the black box

Recent advances give theoretical insight into why deep learning networks are successful.

Looking into the black box

Algorithms & Theory Entertainment

July 29 '20

Algorithm finds hidden connections between paintings at the Met

A team from MIT helped create an image retrieval system to find the closest matches of paintings from different artists and cultures.

Algorithm finds hidden connections between paintings at the Met

Algorithms & Theory Robotics

June 02 '20

New glove lets you incorporate real-life objects into virtual worlds

Algorithms & Theory Robotics Manufacturing

June 01 '20

Giving soft robots senses

In a pair of papers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), two teams enable better sense and perception for soft robotic grippers.

Giving soft robots senses

Algorithms & Theory Programming Languages & Software Engineering

May 06 '20

Visualizing the world beyond the frame

Researchers test how far artificial intelligence models can go in dreaming up varied poses and colors of objects and animals in photos.

Visualizing the world beyond the frame

Algorithms & Theory

April 28 '20

Automating the search for entirely new “curiosity” algorithms

Researchers show that computers can “write” algorithms that adapt to radically different environments better than algorithms designed by humans.

Automating the search for entirely new “curiosity” algorithms

Algorithms & Theory AI & ML Health Care Wireless

April 14 '20

CSAIL device lets doctors monitor COVID-19 patients from a distance

Wireless system helps Boston retirement home care for COVID patients while reducing risk of contagion

CSAIL device lets doctors monitor COVID-19 patients from a distance

Algorithms & Theory

March 24 '20

System trains driverless cars in simulation before they hit the road

Using a photorealistic simulation engine, vehicles learn to drive in the real world and recover from near-crash scenarios.

System trains driverless cars in simulation before they hit the road

Algorithms & Theory AI & ML

March 16 '20

“Doing machine learning the right way”

Professor Aleksander Madry strives to build machine-learning models that are more reliable, understandable, and robust.

“Doing machine learning the right way”

Algorithms & Theory AI & ML Robotics

March 05 '20

Showing robots how to do your chores

By observing humans, robots learn to perform complex tasks, such as setting a table.

Showing robots how to do your chores

Algorithms & Theory Cybersecurity

February 26 '20

Protecting sensitive metadata so it can’t be used for surveillance

System ensures hackers eavesdropping on large networks can’t find out who’s communicating and when they’re doing so.

Protecting sensitive metadata so it can’t be used for surveillance

Automated system can rewrite outdated sentences in Wikipedia articles 1

Algorithms & Theory AI & ML

February 13 '20

Automated system can rewrite outdated sentences in Wikipedia articles

Text-generating tool pinpoints and replaces specific information in sentences while retaining humanlike grammar and style.

Automated system can rewrite outdated sentences in Wikipedia articles

Algorithms & Theory AI & ML Robotics

February 12 '20

“Sensorized” skin helps soft robots find their bearings

Flexible sensors and an artificial intelligence model tell deformable robots how their bodies are positioned in a 3D environment.

“Sensorized” skin helps soft robots find their bearings

Algorithms & Theory AI & ML

February 07 '20

Hey Alexa: Sorry I fooled you

MIT’s new system TextFooler can trick the types of natural-language-processing systems that Google uses to help power its search results, including audio for Google Home

Hey Alexa: Sorry I fooled you

Algorithms & Theory Security & Cryptography

January 31 '20

Giving cryptocurrency users more bang for their buck

Routing scheme boosts efficiency in networks that help speed up blockchain transactions.

Giving cryptocurrency users more bang for their buck

Algorithms & Theory AI & ML Health Care

January 10 '20

How well can computers connect symptoms to diseases?

A new MIT study finds “health knowledge graphs,” which show relationships between symptoms and diseases and are intended to help with clinical diagnosis, can fall short for certain conditions and patient populations. The results also suggest ways to boost their performance.

How well can computers connect symptoms to diseases?

2 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

Impact Areas

Lead

Aleksander Madry

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

14 Project Results

Project

A Simplified and Extensible Cilk Runtime for Research

CilkS is a new runtime system for the Cilk multithreaded programming environment which makes it easy to experiment with new algorithms, data structures, and programming linguistics.

Charles E. Leiserson

Tao Schardl

Leads

Charles E. Leiserson

Tao Schardl

Research Areas

Charles E. Leiserson

Tao Schardl

Project

Distributed Computation in Ant Colonies

Nancy Lynch

Leads

Nancy Lynch

Research Areas

Nancy Lynch

Project

Driver-Friendly Bilateral Control for Suppressing Traffic Instabilities

Vision Group

Self-driving cars themselves can solve traffic problems even without global control.

Leads

Research 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

Is the Casino using a Riffle Shuffle?

Costis Daskalakis

Nick Gravin

Leads

Costis Daskalakis

Nick Gravin

Research Areas

Costis Daskalakis

Nick Gravin

Project

Optimal transport for statistics and machine learning

Linking probability with geometry to improve the theory and practice of machine learning

Justin Solomon

Leads

Justin Solomon

Research Areas

Impact Areas

Justin Solomon

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

Practical Secure Computation

Our goal is to bridge theory and practice to create infrastructure that allow computation and multi-party computation without compromising privacy.

Daniela Rus

Danny Feldman

Leads

Daniela Rus

Danny Feldman

Research Areas

Daniela Rus

Danny Feldman

Project

Reconstructing Neural Circuits from Mammalian Brain

Yaron Meirovitch

Nir Shavit

Leads

Yaron Meirovitch

Nir Shavit

Research Areas

Computational Biology

Impact Areas

Yaron Meirovitch

Nir Shavit

Project

Reliable and Robust Machine Learning

We work towards a principled understanding of the current machine learning toolkit and making this toolkit be robust and reliable.

Aleksander Madry

Leads

Aleksander Madry

Research Areas

Impact Areas

Aleksander Madry

Project

Return of the Byzantine Generals

This project studies new solutions to the Byzantine General Problem and its applications in distributed systems and cryptography.

Srini Devadas

Leads

Srini Devadas

Research Areas

Srini Devadas

Project

Safety Standards for Autonomous Vehicles

Leads

Lucas Liebenwein

Wilko Schwarting

Daniela Rus

Research Areas

Impact Areas

Transportation

Project

Sublinear/Streaming Algorithms for Covering Problem

Our goal is to develop efficient algorithms for the fundamental set cover problem in the massive data model.

Piotr Indyk

Ronitt Rubinfeld

Leads

Piotr Indyk

Ronitt Rubinfeld

Research Areas

Piotr Indyk

Ronitt Rubinfeld

Project

Understanding Convergence of Iterative Algorithms

We are trying to develop theoretical tools that can be used to analyze the convergence of iterative algorithms used for non-convex optimization problems.

Costis Daskalakis

Leads

Costis Daskalakis

Research Areas

Costis Daskalakis

40 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

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

PI
Core/Dual

Costis Daskalakis

Associate Professor

Algorithms, Economics, Game Theory, Statistics, Machine Learning

E costis@csail.mit.edu

T 253-9643

Lead

Is the Casino using a Riffle Shuffle?

Understanding Convergence of Iterative Algorithms

Member

Algorithms, Economics, Game Theory, Statistics, Machine Learning

PI
Core/Dual

Erik Demaine

Professor

Algorithms, theory, computational geometry, complexity

E edemaine@mit.edu

T 253-6871

Lead

Member

Algorithms, theory, computational geometry, complexity

Martin Demaine

Robotics Engineer

E mdemaine@mit.edu

T 253-7953

Barış Ekim

Graduate Student

E ekim@csail.mit.edu

PI
Core/Dual

Shafi Goldwasser

Professor

Theory, cryptography, cybersecurity, complexity

E shafi@csail.mit.edu

T 253-5914

Lead

Complexity Theory Group

Member

Theory, cryptography, cybersecurity, complexity

Noah Golowich

Graduate Student

E nzg@mit.edu

RM 32-G585B

Joanne Hanley

Administrative Assistant II

Administrative Assistant, Theory of Computation

E joanne@csail.mit.edu

T 253-6054

Member

Administrative Assistant, Theory of Computation

Dhiraj Holden

Graduate Student

E dholden@mit.edu

PI
Core/Dual

Piotr Indyk

Professor

Algorithms, theory, computational geometry

E indyk@csail.mit.edu

T 452-3402

Lead

Sublinear/Streaming Algorithms for Covering Problem

Sublinear Algorithms for Massive Data Problems

Member

Algorithms, theory, computational geometry

PI
Core/Dual

Tommi Jaakkola

Professor

Machine learning, natural language processing, genomics

E tommi@csail.mit.edu

T 253-0440

Lead

Aspect-Augmented Adversarial Networks for Domain Adaptation

Learning Strategic Games

Structured Prediction Through Randomization

Interpretability in complex machine learning models

Member

Learning Optimal Interventions

Machine learning, natural language processing, genomics

Siddhartha Jayanti

Graduate Student

E siddhartha@csail.mit.edu

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

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

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

William Kuszmaul

Graduate Student

Research interests in algorithms and high-performance engineering

E kuszmaul@mit.edu

Research interests in algorithms and high-performance engineering

PI
Core/Dual

Charles E. Leiserson

Professor

Algorithms, parallel computing, performance engineering

E cel@csail.mit.edu

T 253-5833

Lead

Supertech Research Group

Performance Engineering of Cache Profilers

CilkPride

A Simplified and Extensible Cilk Runtime for Research

Determining Wikipedia's Influence on Science

Tapir

Member

Safety Standards for Autonomous Vehicles

Algorithms, parallel computing, performance engineering

Lucas Liebenwein

Graduate Student

Student and Researcher | Robotics, AI | Advanced Autonomy

E lucasl@mit.edu

RM 32-376C

Lead

Member

Self-Driving Vehicles

Student and Researcher | Robotics, AI | Advanced Autonomy

PI
Core/Dual

Aleksander Madry

Associate Professor

Theory, algorithms, optimization, robust and reliable ML

E madry@mit.edu

T 324-6739

Lead

Reliable and Robust Machine Learning

Member

Theory, algorithms, optimization, robust and reliable ML

PI
Core/Dual

Albert R. Meyer

Professor Emeritus

Programming languages, theory, complexity, online education

E meyer@csail.mit.edu

T 253-6024

Programming languages, theory, complexity, online education

Slobodan Mitrovic

Postdoctoral Associate

E slobo@mit.edu

PI
Core/Dual

Ankur Moitra

Associate Professor

Theory, algorithms, machine learning, complexity

E moitra@csail.mit.edu

T 253-5876

Lead

Efficient Robust Estimation in High Dimensions

Member

Theory, algorithms, machine learning, complexity

PI
Core/Dual

Ronald Rivest

Institute Professor

Cryptography, cybersecurity, RSA public-key encryption

E rivest@mit.edu

T 253-5880

Lead

Member