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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

7 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

Research Group

Marine Robotics Group

Our projects are centered around the problems of navigation and mapping for autonomous mobile robots operating in underwater and terrestrial environments.

John Leonard

Leads

John Leonard

Research Areas

Impact Areas

Lead

John Leonard

John Leonard

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

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

Sensing, Learning and Inference

We develop scalable algorithms for analysis of complex, high-dimensional data.

+6

John Fisher

Leads

John Fisher

Research Areas

Graphics & Vision

Impact Areas

Internet of Things

Lead

John Fisher

John Fisher

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

6 Project Results

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

Computational Multicopter Design

Computer Graphics Group

A system that can help you to design our own drone!

Tao Du

Leads

Tao Du

Research Areas

Graphics & Vision

Impact Areas

Tao Du

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

Printable Hydraulics

Distributed Robotics Laboratory

Printable Hydraulics allows fluid-actuated robots to be automatically fabricated using 3D printers.

Youbin Kim

Leads

Research Areas

Impact Areas

Youbin Kim

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

Supervising Robots with Muscle and Brain Signals

Distributed Robotics Laboratory

What if we could control robots more intuitively, using just hand gestures and brainwaves?

Joseph DelPreto

Leads

Joseph DelPreto

Research Areas

Human-Computer Interaction

Impact Areas

Joseph DelPreto

3 People Results

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.

Michael Foshey

Mechanical Engineer/Project Manager

Additive Manufacturing, Robotics, Digital Fabrication

E mfoshey@mit.edu

RM

Additive Manufacturing, Robotics, Digital Fabrication

Ramin Hasani

Postdoctoral Associate

Machine learning Scientist

E rhasani@csail.mit.edu

Machine learning Scientist

7 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

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