Faculty

02/17/2023 - ​The Alfred P. Sloan Foundation announced today the early-career researchers across the U.S. and Canada who are recipients of the 2023 Sloan Research Fellowship, including UT Computer Science Assistant Professor Greg Durrett. ​Based on a "candidate's research accomplishments, creativity, and potential to become a leader in their field," independent panels composed of senior scholars select 126 recipients every year out of more than a thousand who are nominated by fellow scientists.

02/16/2023 - The Association for the Advancement of Artificial Intelligence (AAAI) has selected Risto Miikkulainen as one of 11 fellows for 2023. Founded in 1990, AAAI's Fellows Program seeks to highlight the individuals who contribute greatly to the field of AI. Miikkulainen was honored for "significant contributions to neuroevolution techniques and applications."

02/06/2023 - The IEEE Computer Society has selected Keshav Pingali to receive the 2023 IEEE CS Charles Babbage Award for his "contributions to high-performance compilers and graph computing." At The University of Texas at Austin, Pingali is the W.A. "Tex" Moncrief Chair of Grid and Distributed Computing and a professor in the Department of Computer Science and core faculty in the Oden Institute for Computational Engineering and Sciences.

02/01/2023 - UT Computer Science Professor Scott Aaronson is one of six faculty in The University of Texas at Austin, to be elected as a fellow of the American Association for the Advancement of Science (AAAS)— the world's largest general scientific society. His research interests center around the capabilities and limits of quantum computers, and computational complexity theory more generally. He has won numerous awards throughout his career, most recently the 2020 Association for Computing Machinery Prize for groundbreaking contributions to quantum computing.

12/14/2022 - For decades, natural language processing (NLP) has provided methods for computers to understand language in a way that mimics humans. Since they are built on transformers, complex neural network layers, these large language models' decision making processes are usually incomprehensible to humans and require large amounts of data to be trained properly. In the past, researchers have tried to remedy this by having models explain their decisions by providing rationales, short excerpts of data that contributed most to the label.

11/14/2022 - It is with great sadness that we inform the scientific community of the passing of an international giant. Dana Ballard passed away on Nov 3rd, 2022, at the age of 76.

11/09/2022 - Each year, the College of Natural Sciences Teaching Excellence Award recognizes educators who provide outstanding education focused on research that enriches the experience of students.

10/20/2022 - Autonomous robots will soon rove the buildings and streets of The University of Texas at Austin campus. But unlike other commercial delivery services, this fleet of robots will help researchers understand and improve the experience of pedestrians who encounter them.

09/23/2022 - As the technological world advances, it has become increasingly difficult for the speed of computers to improve. UT Computer Science Professor Dr. Chris Rossbach's research in field-programmable gate array (FPGA) virtualization has made significant strides in the development of a more efficient computing infrastructure.

08/04/2022 - Privacy has become increasingly valuable and rare as technology has become more closely integrated with our lives. Private information retrieval (PIR) protocols allow you to retrieve information through an encoded query while also protecting your personal information. Our current security standard online can be viewed as a “no-privacy baseline,” which means the vast majority of our online information retrieval isn’t protected by any of these protocols. Cryptographers like UT Computer Science professor David Wu are building innovative solutions that support this growing preference for online privacy.