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The goal of Feizi’s project is to design metrics that evaluate a defense’s effectiveness of robustness, scalability in deep networks and transferability across models.

The new program supports up-and-coming researchers on the University of Maryland campus.

Boyd-Graber and his team are presenting two papers on how to quickly train aging AI systems to sift through medical and emergency data.

A paper by Daochen Wang (in photo) and Andrew Childs in QuICS explores current boundaries—and possible future advances—involving exponential quantum speedups.

The project will receive $450K over the next three years as part of the Air Force Office of Scientific Research Young Investigator Research Program.

Feizi is designing Reverse Engineer Deceptions (RED), a program that will not only be able to identify the origin of the attack and its sophistication level, but also the most effective defense to use against future attacks.

He aims to develop new tools that will enable blind and visually impaired coders to create visual layout and frontend programs independently.

She is being recognized for her comprehensive body of work within the field of data visualization, including her contributions to evaluation, benchmarks and case studies, and her specific research focus on event sequence visualization.

Victor Albert and Michael Gullans arrived this fall and are now embedded within the QuICS research community.

The workshop offers a team-based setting that provides a positive intellectual, social and emotional environment for participants interested in computing.