With videos now making up more than 80% of all consumer internet traffic, even the smallest improvements in compression algorithms can dramatically impact our ability to store and share information.

“It has been speculated for a long time that neural networks will ultimately revolutionize data compression technologies. Recently, such attempts have proved successful,” says Stephan Mandt, an assistant professor of computer science and statistics in UCI’s Donald Bren School of Information and Computer Sciences (ICS). Mandt has been at the forefront of this work. “Our group at UCI has been pioneering research into using neural networks to compress data.”

Last year, in honor of Black History Month, the Donald Bren School of Information and Computer Sciences (ICS) highlighted pioneers in science and technology (see Part I and Part II of the post). This year, we’ve pulled together a list of resources, including on-campus groups here at UCI. We also list some nationwide organizations and books that focus on diversity and race in technology, as well as spotlight some Black leaders in computer science and engineering, both on and off campus.

On Jan. 26, 2022, UCI announced seven new faculty members had been named fellows of the American Association for the Advancement of Science (AAAS) — an association that “seeks to advance science, engineering, and innovation throughout the world for the benefit of all people.” AAAS Fellows are “a distinguished cadre of scientists, engineers and innovators who have been recognized for their achievements across disciplines, from research, teaching, and technology, to administration in academia, industry and government, to excellence in communicating and interpreting science to the public.”

Among the seven new inductees at UCI are four researchers from the Donald Bren School of Information and Computer Sciences (ICS): Rina Dechter of the Department of Computer Science, Paul Dourish of the Department of Informatics, Annie Qu of the Department of Statistics, and Padhraic Smyth of both the Department of Computer Science and Department of Statistics. Congratulations to these four esteemed researchers for achieving this lifetime honor.

Statistics Ph.D student Qi Xu’s paper, “Crowdsourcing utilizing subgroup structures of latent factor modeling,” was one of five winning papers recognized recently by the Statistical Learning and Data Science (SLDS) Section of the American Statistical Association. The SLDS hosts an annual student paper competition that is extremely competitive, this year selecting only five student papers from more than 85 submissions. As one of the award recipients, Xu’s paper will be presented at the 2022 Joint Statistical Meetings in August during a special topic-contributed session. Xu’s current research interests are latent factor modeling and deep learning, and their application in crowdsourcing and personalized medicine. His thesis advisor is Chancellor’s Professor of Statistics Annie Qu.