December 28, 2017
Andrew K. McCallum (URCS Ph.D. 1996) has been named a Fellow of the Association for Computing Machinery, "For contributions to machine learning with structured data, and innovations in scientific communication."
December 20, 2017
It is with great sadness that the Computer Science department shares the news of the death of Dr. Tao Li '04, a graduate of the University of Rochester's Computer Science PhD program. Dr. Li is remembered as a truly brilliant computer science researcher, extraordinary teacher, vibrant mentor, caring colleague, and beloved friend.
October 5, 2017
In four years since becoming an assistant professor at the University of Rochester, Ehsan Hoque has earned an impressive set of honors.
Prof. Ehsan Hoque has been named to a three-year term as the the Asaro Biggar Family Fellow in Data Science
August 22, 2017
Prof. Ehsan Hoque has been named to a three-year term as the Asaro Biggar Family Fellow in Data Science. This fellowship was created by Stephen Biggar '92 and Elisabeth Asaro-Biggar '92 to support "researchers in varied disciplines using data science methods to frame, analyze, and answer the big questions in their fields." The fellowship allows the University to honor and encourage outstanding faculty early in their academic careers at Rochester, nurturing them on the path to full professor.
March 21, 2017
For many decades, the diversity in computer science nationally has been disproportionately lower than in other science disciplines. In an effort to change that at Rochester, many steps have been taken to help build a better community for women and underrepresented minorities in the Department of Computer Science at Rochester.
March 16, 2017
Sandhya Dwarkadas was recently featured in Computing Research News, a publication of the Computing Research Association. The article entitled "Expanding the Pipeline" discusses Sandhya's efforts are Professor and Chair of the Computer Science Department.
February 20, 2017
Jiebo Luo and Yu Wang did not set out to predict who would win the 2016 U.S. presidential election. However, their exhaustive, 14-month study of each candidate’s Twitter followers–enabled by machine learning and other data science tools–offers tantalizing clues as to why the race turned out the way it did. “We wanted to understand how each of the candidate’s campaigns evolved, and be able to explain why someone won or lost,” says Professor Luo of computer science.