Data

William Deringer of STS has his first book coming out in February about how quantitative economic arguments gained hold in the modern world.

When numbers started counting

New book by MIT assistant professor chronicles the birth of statistical arguments in public debate.

February 5, 2018

K. Daron Acemoglu, the Elizabeth and James Killian Professor of Economics at MIT, is a leading thinker on the labor market implications of artificial intelligence, robotics, automation, and new technologies.

3Q: Daron Acemoglu on technology and the future of work

"We need to look to the past in the face of modern innovations in machine learning, robotics, artificial intelligence, big data, and beyond," says the economist.

February 1, 2018

Clipart of someone with laptop and lab equipment

Startup makes labs smarter

Platform connects individual pieces of lab equipment, compiles data in the cloud for speedier, more accurate research.

January 25, 2018

Originally from the small town of Cluny, in the Burgundy region of France, Philippe Rigollet made the move to MIT in 2014.

From undisciplined to interdisciplinary

Math professor Philippe Rigollet, once a “not very disciplined” student, moves between computer science and statistics.

January 21, 2018

A new machine-learning system for analyzing materials “recipes” uses a variational autoencoder, which squeezes data (left-hand circles) down into a more compact form (center circles) before attempting to re-expand it into its original form (right-hand circles). If the autoencoder is successfully trained, the compact representation will capture the data’s most salient characteristics.

Can computers help us synthesize new materials?

Machine-learning system finds patterns in materials “recipes,” even when training data is lacking.

December 21, 2017

An illustration of real-world behavioral commonalities in raw data of transactions.

Inventing the “Google” for predictive analytics

Platform analyzes big data to answer plain-language business queries in minutes instead of months.

December 19, 2017

To solve complex problems, data scientists must shepherd their raw data through a series of steps, each one requiring many human-driven decisions. The last step in the process, deciding on a modeling technique, is particularly crucial.

Auto-tuning data science: New research streamlines machine learning

A new automated machine-learning system performs as well or better than its human counterparts — and works 100 times faster.

December 19, 2017

“One of our tasks for 2018 is to figure out how to leverage all of this momentum and to build and maintain this very powerful network of data scientists, activists, and organizers,” said MIT mathematics graduate student Lucas Mason-Brown, who organized the recent Data for Black Lives (D4BL) conference, held at the Media Lab.

Calculating the cost of tech-fueled discrimination

Math graduate student’s Data for Black Lives conference provides numbers behind the technologies that enable exclusion.

December 13, 2017

Next year, Olivia Zhao will attend Oxford University to earn a Master’s degree in economics as a Marshall Scholar. After that, she hopes to earn a PhD in economics and work in a university or at an institution such as the Chicago Federal Reserve, to research public policy from an economics perspective.

Seeking the stories behind the data

MIT Senior Olivia Zhao will study economics as a Marshall Scholar.

December 10, 2017

MIT spinout Portal Instruments has landed a commercialization deal for a smart, needle-free injection device that could reduce the pain and anxiety associated with needle injections, shorten administration time, and improve patient adherence.

Startup’s needle-free drug injector gets commercialization deal

Collaboration with pharmaceutical giant will bring smart jet-injection device to market.

December 7, 2017

To determine what products a given customer might like, recommendation systems at websites such as Amazon and Netflix look for other customers who have assigned similar ratings to a similar range of products, and extrapolate from there.

Try this! Researchers devise better recommendation algorithm

Improved recommendation algorithm should work especially well when ratings data are “sparse.”

December 6, 2017

Richard Nielsen’s book, “Deadly Clerics: Blocked Ambition and the Paths to Jihad,” finds a certain portion of Muslim clerics who end up advocating for jihad — war against Islam’s foes — started out as mainstream clerics looking for state-sponsored jobs where they could use their intellectual training, only to become unemployed, disenchanted, and radicalized.

Why some Muslim clerics become jihadists

In his new book, political scientist Richard Nielsen proposes a “blocked ambition” hypothesis.

November 9, 2017

MIT Professor Daniela Rus (right), director of the Computer Science and Artificial Intelligence Laboratory, speaks with Alphabet chairman Eric Schmidt.

Summit discusses impact of machines on jobs, productivity, and the global economy

Two-day “AI and the Future of Work” summit at MIT focused on the artificial intelligence revolution and the workplace.

November 7, 2017

A new MIT computer system speeds computations involving “sparse tensors,” multidimensional data arrays that consist mostly of zeroes.

Faster big-data analysis

System for performing “tensor algebra” offers 100-fold speedups over previous software packages.

October 30, 2017

“I think that the concept of massive and open data science can be really leveraged for areas where there’s a strong social impact but not necessarily a single profit-making or government organization that is coordinating responses,” MIT graduate student Micah Smith says about FeatureHub.

Crowdsourcing big-data analysis

Web-based system automatically evaluates proposals from far-flung data scientists.