Faculty

10/28/2019 - People turn to many different sources for clothing style advice, from magazines to best friends to Instagram. Soon, though, you may be able to ask your smartphone. A University of Texas at Austin computer science team, in partnership with researchers from Cornell Tech, Georgia Tech and Facebook AI Research, has developed an artificial intelligence system that can look at a photo of an outfit and suggest helpful tips to make it more fashionable. Suggestions may include tweaks such as selecting a sleeveless top or a longer jacket.

10/15/2019 - Dr. Scott Niekum, Texas Computer Science professor and director of the Personal Autonomous Robotics Lab (PeARL), has received a Young Investigator Award from the Air Force Office of Scientific Research.

07/10/2019 - TXCS associate professor of instruction Alison Norman has been selected to receive the 2019 Regents’ Outstanding Teaching Award. Given by the Board of Regents of The University of Texas System, this honor is one of the nation’s largest monetary teaching recognitions in higher education.

06/19/2019 - Marc G Airhart | College of Natural Sciences Computer scientist Brent Waters of The University of Texas at Austin has been selected as a 2019 Simons Investigator in Theoretical Computer Science by the Simons Foundation, for his work in cryptography and computer security.

06/17/2019 - Calvin Lin, a Texas Computer Science Distinguished Teaching Professor, won the 2019-20 William David Blunk Memorial Professorship. The professorship recognizes a member of the faculty who has demonstrated an exceptional record in undergraduate teaching, and who shows special interest in and on behalf of undergraduate students.

05/16/2019 - Computer scientists at The University of Texas at Austin have taught an artificial intelligence agent how to do something that usually only humans can do—take a few quick glimpses around and infer its whole environment, a skill necessary for the development of effective search-and-rescue robots that one day can improve the effectiveness of dangerous missions.

05/10/2019 - Is my code fast? Can it be faster? Scientific computing, machine learning, and data science are about solving problems that are compute intensive. Choosing the right algorithm, extracting parallelism at various levels, and amortizing the cost of data movement are vital to achieving scalable speedup and high performance.

05/06/2019 - Peter Stone, a professor of computer science at The University of Texas at Austin, has won the Minnie Stevens Piper Teaching Award, which celebrates outstanding postsecondary teaching. Since 1958, the Minnie Stevens Piper Foundation, a non-profit, charitable corporation focused on postsecondary education in Texas, has selected excellent educators from four- and two-year institutions from across Texas to be named "Piper Professors" for their superior teaching at the college level. Stone holds the David Bruton, Jr.

04/30/2019 - There is a certain “grow fast or die slow” paradigm in the present-day computing industry. Software and technological innovations are in a period of massive growth and flux—change is so rapid that even today’s laws are lagging behind. Texas Computer Science and Texas Law professors argue that under current circumstances, it is also important to consider the ways in which the legal field is evolving to adapt to these technological changes as well as examine the further ethical implications of computing.

04/19/2019 - Water, sunlight, nutrients—these ingredients are essential for plant growth. However, these basic ingredients don’t always yield the ideal plant. In fact, optimizing these variables is complicated, causing some plants to fall flat on flavor. Machine learning can help.