Data

Left to right: senior research scientist David Clark, graduate student Cecilia Testart, and postdoc Philipp Richter

Using machine learning to hunt down cybercriminals

Model from the Computer Science and Artificial Intelligence Laboratory identifies “serial hijackers” of internet IP addresses.

October 8, 2019

TX-GAIA is housed inside of a new EcoPOD, manufactured by Hewlett Packard Enterprise, at the site of the Lincoln Laboratory Supercomputing Center in Holyoke, Massachusetts.

Lincoln Laboratory's new artificial intelligence supercomputer is the most powerful at a university

TX-GAIA is tailor-made for crunching through deep neural network operations.

September 27, 2019

New MIT study identifies “model” Indian cities that effectively preserve citizen privacy, while leveraging their data to improve government efficiency.

How cities can leverage citizen data while protecting privacy

Study offers models for preserving the privacy of citizens while using their data to improve government services.

September 25, 2019

"Scientists are often motivated by factors other than wages,” says Carolyn Stein, "but many insights from labor economics still help us understand how the field of science functions. Incentive and career concerns still matter. And risk is a big concern.”

Meet Carolyn Stein: Researching the economics of science

MIT PhD student explores the impact of scientists being "scooped" when a competing research team publishes results first, a concern for many disciplines.

September 23, 2019

3 Questions: Why sensing, why now, what next?

Brian Anthony, co-leader of SENSE.nano, discusses sensing for augmented and virtual reality and for advanced manufacturing.

September 20, 2019

Using just the first 15 minutes of a patient's electrocardiogram (ECG) signal, an MIT system produces a score that places patients into different risk categories.

Using machine learning to estimate risk of cardiovascular death

CSAIL system uses a patient's ECG signal to estimate potential for cardiovascular death.

September 12, 2019

A novel system by MIT researchers automatically “learns” how to allocate data-processing operations across thousands of servers.

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.

August 21, 2019

MIT researchers have developed a “risk-aware” model that could improve the performance of cloud-computing networks across the U.S.

Using Wall Street secrets to reduce the cost of cloud infrastructure

“Risk-aware” traffic engineering could help service providers such as Microsoft, Amazon, and Google better utilize network infrastructure.

August 18, 2019

Associate professor Tracy Slatyer focuses on searching through telescope data for signals of mysterious phenomena such as dark matter, the invisible stuff that makes up more than 80 percent of the matter in the universe but has only been detected through its gravitational pull. In her teaching, she seeks to draw out and support a new and diverse crop of junior scientists.

Data-mining for dark matter

Tracy Slatyer hunts through astrophysical data for clues to the invisible universe.

August 15, 2019

The MIT Press releases a comprehensive report on open-source publishing software

Report catalogs, analyzes available open-source publishing software; warns open publishing must grapple with siloed development and community-owned ecosystems.

August 8, 2019