The system they developed eliminates a source of bias in simulations, leading to improved algorithms that can boost the performance of applications.
With the right building blocks, machine-learning models can more accurately perform tasks like fraud detection or spam filtering.
Strengthening trust in machine-learning models
Associate Professor Tamara Broderick and colleagues build a “taxonomy of trust” to identify where confidence in the results of a data analysis might break down.
Computers that power self-driving cars could be a huge driver of global carbon emissions
Study shows that if autonomous vehicles are widely adopted, hardware efficiency will need to advance rapidly to keep computing-related emissions in check.
Six With Ties to MIT Honored as ACM Fellows
Six distinguished scientists with ties to MIT were recognized “for significant contributions in areas including cybersecurity, human-computer interaction, mobile computing, and recommender systems among many other areas.”
Investigating at the interface of data science and computing
Guy Bresler builds mathematical models to understand multifaceted, interdisciplinary engineering problems that have far-reaching applications.
Department of EECS announces 2022 promotions
The Department of EECS is proud to announce the following promotions and hire: To Associate Professor with tenure Guy Bresler is being promoted to Associate Professor with tenure, effective July 1, 2022. Bresler…
Living better with algorithms
Graduate student Sarah Cen explores the interplay between humans and artificial intelligence systems, to help build accountability and trust.
On the road to cleaner, greener, and faster driving
Researchers use artificial intelligence to help autonomous vehicles avoid idling at red lights.
Asada, Daniel, Shah Named Fellows of IEEE
Among the newly selected Fellows of the Institute of Electrical and Electronics Engineers (IEEE) are three members of the MIT community: Harry Asada, Ford Professor of Engineering in…