05/16/2016 - With an advance that one cryptography expert called a "masterpiece," University of Texas at Austin computer scientists have developed a new method for producing truly random numbers, a breakthrough that could be used to encrypt data, make electronic voting more secure, conduct statistically significant polls and more accurately simulate complex systems such as Earth's climate.
04/28/2016 - Image Lorenzo Alvisi has been selected as one of just seven new members of The University of Texas at Austin's
04/15/2016 - David Zuckerman has been selected as a Simons Investigator in Theoretical Computer Science. David's research focuses primarily on pseudorandomness and the role of randomness in computing. He is best known for his work on randomness extractors and their applications. His other research interests include coding theory, distributed computing, cryptography, inapproximability, and other areas of complexity theory.
04/01/2016 - Chandrajit Bajaj has been selected as a Fellow of the Society for Industrial and Applied Mathematics (SIAM) "for fundamental contributions to applied mathematics algorithms in geometric modeling, imaging science, bioinformatics, and data visualization." SIAM Fellows are designated each year to recognize members of the community for their distinguished contributions to the disciplines of applied mathematics, computational science and related fields.
03/21/2016 - In addition to his role as a professor, UT Computer Science’s Robert van de Geijn is the Director of the ICES’ Science of High-Performance Computing (SHPC) Group.
03/09/2016 - AlphaGo, a program that plays what many consider the most difficult of board games, Go, has just won the first of five matches against the world's top human player. The series is scheduled to continue through March 12. Developed by Google's DeepMind subsidiary, AlphaGo has already beaten the European Go champion. A few days before the latest competition, we asked Risto Miikkulainen, an artificial intelligence researcher at the University of Texas at Austin, for his thoughts on this historic contest.
03/04/2016 - Image
02/16/2016 - Professor Peter Stone has been selected as the recipient of the 2016 ACM/SIGAI Autonomous Agents Research Award. Stone's work is exceptional in both its breadth and depth in multiagent systems. Some of his most influential work has been in reinforcement learning and multiagent learning as applied to robot soccer, autonomous traffic management, and trading agents.
01/05/2016 - President Fenves recently announced Calvin Lin as a recipient of the 2015-16 President's Associates Teaching Excellence Award. This award, established in the fall of 1980, recognizes the consistent level of excellence that Calvin has achieved in teaching undergraduates within the Department of Computer Science.