Awards & Honors
UT Computer Science graduate student Siavash Mirarab was awarded Honorable Mention for the 2015 ACM Doctoral Dissertation Award. Mirarab’s dissertation, Novel Scalable Approaches for Multiple Sequence Alignment and Phylogenomic
Lorenzo Alvisi has been selected as one of just seven new members of The University of Texas at Austin's Academy of Distinguished Teachers for his sustained and significant contributions to education. Lorenzo will be part of a central core of teachers who serve as a resource and aim to be an inspiration for other teachers, and promote a sense of
2015 Recipients Made Contributions in Areas Including Artificial Intelligence, Software Systems and Encryption
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.
The University of Texas Department of Computer Science (UTCS) has been selected as one of two NCWIT Second Place NEXT Award winners. The department has won this accolade for its achievements in recruiting and retaining women into UTCS and for it’s successful allocation of resources towards building a department-wide culture of support and community for women.
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
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.