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1 News Results matching all criteria

Barbara Liskov 2

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

14 Group Results

Research Group

Algorithms Group

We devise new mathematical tools to tackle the increasing difficulty and importance of problems we pose to computers.

Leads

Costis Daskalakis

Erik Demaine

Michael Goemans

Piotr Indyk

David Karger

Jonathan Kelner

Tom Leighton

Charles E. Leiserson

Aleksander Madry

Ankur Moitra

Ronitt Rubinfeld

Nir Shavit

Ryan Williams

Virginia Vassilevska Williams

Research Areas

Algorithms & Theory

Impact Areas

Lead

Costis Daskalakis

Erik Demaine

Michael Goemans

Piotr Indyk

David Karger

Jonathan Kelner

Tom Leighton

Charles E. Leiserson

Aleksander Madry

Ankur Moitra

Ronitt Rubinfeld

Nir Shavit

Ryan Williams

Virginia Vassilevska Williams

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.

+1

Una-May O'Reilly

Leads

Una-May O'Reilly

Research Areas

Security & Cryptography

Impact Areas

Lead

Una-May O'Reilly

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.

+6

Una-May O'Reilly

Leads

Una-May O'Reilly

Research Areas

Computational Biology

Programming Languages & Software Engineering

Impact Areas

Lead

Una-May O'Reilly

Una-May O'Reilly

Research Group

Center for Brains, Minds and Machines

Our main goal is developing a computationally based understanding of human intelligence and establishing an engineering practice based on that understanding.

Tomaso Poggio

Leads

Tomaso Poggio

Research Areas

Computational Biology

Impact Areas

Lead

Tomaso Poggio

Tomaso Poggio

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.

+6

Howard Shrobe

Leads

Howard Shrobe

Research Areas

Human-Computer Interaction

Security & Cryptography

Systems & Networking

Impact Areas

Lead

Howard Shrobe

Howard Shrobe

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

Computational Biology

Impact Areas

Lead

Aude Oliva

Aude Oliva

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

+2

David Karger

Leads

David Karger

Research Areas

Algorithms & Theory

Human-Computer Interaction

Programming Languages & Software Engineering

Impact Areas

Internet of Things

Lead

David Karger

Lea Verou

David Karger

Research Group

Lecturers

Lecturers in CSAIL

Leads

Research Areas

Algorithms & Theory

Security & Cryptography

Systems & Networking

Impact Areas

Research Group

Multicore Algorithmics

We develop techniques for designing, implementing, and reasoning about multiprocessor algorithms, in particular concurrent data structures for multicore machines and the mathematical foundations of the computation models that govern their behavior.

Nir Shavit

Leads

Nir Shavit

Research Areas

Algorithms & Theory

Systems & Networking

Impact Areas

Lead

Nir Shavit

Nir Shavit

Research Group

Multimodal Understanding Group

Our objective is to build techniques, software, and hardware that enable natural interaction with
computation.

Randall Davis

Leads

Randall Davis

Research Areas

Algorithms & Theory

Human-Computer Interaction

Impact Areas

Lead

Randall Davis

Randall Davis

Research Group

Quantum Information Science Group

Our research interests center around the capabilities and limits of quantum computers, and computational complexity theory more generally.

Peter Shor

Leads

Peter Shor

Research Areas

Algorithms & Theory

Impact Areas

Lead

Peter Shor

Peter Shor

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

Human-Computer Interaction

Programming Languages & Software Engineering

Security & Cryptography

Impact Areas

Lead

Daniel Jackson

Daniel Jackson

Research Group

Theory of Distributed Systems Group

We work on a wide range of problems in distributed computing theory. We study algorithms and lower bounds for typical problems that arise in distributed systems---like resource allocation, implementing shared memory abstractions, and reliable communication.

Nancy Lynch

Leads

Nancy Lynch

Research Areas

Algorithms & Theory

Impact Areas

Lead

Nancy Lynch

Nancy Lynch

Research Group

Weiss Laboratory for Synthetic Biology

The Weiss Lab seeks to create integrated biological systems capable of autonomously performing useful tasks, and to elucidate the design principles underlying complex phenotypes.

Leads

Research Areas

Computational Biology

Systems & Networking

Impact Areas

9 Project Results

Project

Active Learning of Models for Planning

Learning and Intelligent Systems

Machine Learning

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

Algorithms & Theory

Human-Computer Interaction

Impact Areas

Leslie Kaelbling

Tomas Lozano-Perez

Project

Alloy

Software Design Group

Human-Computer Interaction Community of Research

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

Human-Computer Interaction

Programming Languages & Software Engineering

Security & Cryptography

Impact Areas

Daniel Jackson

Project

Bayesian Optimization for Global Optimization of Expensive Black-box Functions

Machine Learning

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

Algorithms & Theory

Impact Areas

Project

Better Models for Ride-Sharing

Distributed Robotics Laboratory

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

Leads

Research Areas

Algorithms & Theory

Systems & Networking

Impact Areas

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

Algorithms & Theory

Human-Computer Interaction

Programming Languages & Software Engineering

Impact Areas

Neil Thompson

Charles E. Leiserson

Project

Distributed Robot Garden

Distributed Robotics Laboratory

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

Leads

Joseph DelPreto

Lindsay Sanneman

Daniela Rus

Research Areas

Algorithms & Theory

Human-Computer Interaction

Programming Languages & Software Engineering

Impact Areas

Project

Drones that Drive

Distributed Robotics Laboratory

Multi-robot path planning for robot swarms that can both fly and drive

Leads

Research Areas

Algorithms & Theory

Impact Areas

Project

PrivacyML - A Privacy Preserving Framework for Machine Learning

Decentralized Information Group

Cognitive AI Community of Research

Computing & Society Community of Research

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

Security & Cryptography

Impact Areas

Internet of Things

Lalana Kagal

Vaikkunth Mugunthan

Project

Robot Compiler

Distributed Robotics Laboratory

The Robot Compiler allows non-engineering users to rapidly fabricate customized robots, facilitating the proliferation of robots in everyday life. It thereby marks an important step towards the realization of personal robots that have captured imaginations for decades.

Leads

Joseph DelPreto

Andrew Spielberg

Daniela Rus

Research Areas

Algorithms & Theory

Human-Computer Interaction

Impact Areas

Internet of Things

8 People Results

R. David Edelman

Director, Project on Technology, Economy & National Security

Machine learning, cybersecurity, governance

E rde@mit.edu

T 258-6389

Machine learning, cybersecurity, governance

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

David Karger

Professor

Helping people manage information

E karger@csail.mit.edu

T 258-6167

RM

Lead

Human-Computer Interaction

Algorithms 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

Theory of Computation Community of Research

Systems Community of Research

Helping people manage information

PI
Core/Dual

Charles E. Leiserson

Professor

Algorithms, parallel computing, performance engineering

E cel@csail.mit.edu

T 253-5833

RM

Lead

Supertech Research Group

Algorithms Group

Performance Engineering of Cache Profilers

A Simplified and Extensible Cilk Runtime for Research

Determining Wikipedia's Influence on Science

Member

Theory of Computation Community of Research

Systems Community of Research

Algorithms, parallel computing, performance engineering

PI
Core/Dual

Albert R. Meyer

Professor Emeritus

Programming languages, theory, complexity, online education

E meyer@csail.mit.edu

T 253-6024

RM

Programming languages, theory, complexity, online education

PI
Core/Dual

Una-May O'Reilly

Principal Research Scientist

Applied AI and ML in cybersecurity, healthcare, education

E unamay@csail.mit.edu

T 253-6437

RM

Lead

Anyscale Learning for All ALFA

Applied Machine Learning Community of Research

Adversarial Cyber Security

GIGABEATS: Data science for medical sensor data

MOOC Learner Project: Data science for e-learning

Member

Cognitive AI Community of Research

Applied AI and ML in cybersecurity, healthcare, education

Yu Wang

Graduate Student

E wangyu9@mit.edu

RM 32-D475A

Member

Geometric Data Processing Group

Geometry and topology for scientific computing and shape analysis

PI
Core/Dual

Ryan Williams

Associate Professor

Theory, algorithms, complexity.

E rrw@mit.edu

RM

Lead

Complexity Theory Group

Algorithms Group

Member

Theory of Computation Community of Research

Theory, algorithms, complexity.

9 News Results

Deep learning

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

Datacenters 1

Algorithms & Theory AI & ML Energy

August 28 '19

Artificial intelligence could help data centers run far more efficiently

MIT system “learns” how to optimally allocate workloads across thousands of servers to cut costs, save energy.

Artificial intelligence could help data centers run far more efficiently

Barbara Liskov 2

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

Flash 1

Algorithms & Theory Energy

April 02 '19

Advance boosts efficiency of flash storage in data centers

New architecture promises to cut in half the energy and physical space required to store and manage user data.

Advance boosts efficiency of flash storage in data centers

3-d shapes 1

Algorithms & Theory AI & ML Graphics & Vision Energy Entertainment Manufacturing

December 10 '18

Teaching machines to see in 3-D

CSAIL’s approach uses algorithms and “2.5-D” sketches to let computers visualize images from any perspective

Teaching machines to see in 3-D

Thomas Bourgeat, Andrew Wright, Arvind and Sizhou Zhang

Computer Architecture Security & Cryptography Cybersecurity Energy

October 22 '18

Opening up open-source to design better chips

MIT CSAIL system lets users change one part of a processor’s design without impacting the others

Opening up open-source to design better chips

drone1

Algorithms & Theory Robotics Energy Manufacturing Transportation

February 12 '18

Programming drones to fly in the face of uncertainty

CSAIL's NanoMap system enables drones to avoid obstacles while flying at 20 miles per hour, by more deeply integrating sensing and control.

Programming drones to fly in the face of uncertainty

bbva1

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

Image: Jose-Luis Olivares

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