01/15/2014 - Professor Peter Stone spoke with Joe Palca this morning on NPR's Morning Edition about taking his "passion for soccer into the lab" in a segment aptly titled "Peter Stone Can't Get Enough Of Robots Playing Soccer."
01/08/2014 - Kurt Dresne, one of Professor Peter Stone's former UT Computer Science graduate student spoke with NPR's Robert Siegel recently about his thesis research on autonomous intersection management in a segment called "To Make Intersections Smarter, We Need Cars To Be Smarter, Too."
01/08/2014 - Three faculty members from The University of Texas at Austin have been selected to receive Presidential Early Career Awards for Scientists and Engineers, the highest honor bestowed by the United States government on science and engineering professionals in the early stages of their research careers.
12/20/2013 - UT Computer Science is excited to welcome four new faculty members coming to campus in 2014. They all have incredibly impressive credentials and research experience, and we’re extremely grateful that they have chosen to join our family.
12/10/2013 - Professor David Zuckerman has been elected to be an ACM Fellow for his contributions to randomness extraction, pseudo randomness, and their role in complexity theory.
12/09/2013 - Professor Dana Ballard, and his co-author Michael Swain, have won the Helmholtz Test-of-Time award.
12/09/2013 - Dana Ballard has been selected to receive the 2014 Distinguished Cognitive Scientist Award from the University of California, Merced.
11/25/2013 - Two of our distinguished faculty, Chandra Bajaj and Inderjit Dhillon, have been elected IEEE Fellows.
11/20/2013 - Associate Professor Lili Qiu has been recognized as one of the Association for Computing Machinery's (ACM) 2013 Distinguished Scientists. Her research focus is on internet and wireless networking. Qiu's current projects include Wireless Network Management, MIMO, and Content Distribution in Mobile Networks.
11/14/2013 - A team of researchers at Rice University, Baylor College of Medicine (BCM) and the University of Texas at Austin are working together to develop new statistical tools that can find clues about cancer that are hidden like needles in enormous haystacks of raw data.