Research

05/20/2024 - The National Science Foundation (NSF) has announced the recipients of its prestigious Graduate Research Fellowships (NSF GRFP) for 2024, and students from the Department of Computer Science at The University of Texas at Austin's College of Natural Sciences (CNS) have been prominently recognized. This year, four Computer Science students were honored with fellowships or honorable mentions, highlighting their outstanding contributions and potential in various cutting-edge research areas.

05/17/2024 - Researchers are using corrupted data to help generative AI models avoid the misuse of images under copyright. Powerful new artificial intelligence models sometimes, quite famously, get things wrong — whether hallucinating false information or memorizing others’ work and offering it up as their own. To address the latter, researchers led by a team at The University of Texas at Austin have developed a framework to train AI models on images corrupted beyond recognition.

05/16/2024 - Guide-dog users and trainers can provide insight into features that make robotic helpers useful in the real world.

05/06/2024 - Music has always had the power to stir our emotions, from the exhilaration of a fast-paced rock anthem to the melancholy of a soulful ballad. But, could the music we listen to also affect how we make decisions, especially in our interactions with robots? This intriguing question lies at the heart of a study conducted by UT Austin Assistant Professor Elad Liebman and Professor Peter Stone.

04/19/2024 - UT Computer Science is at the forefront of robotics innovation, aiming to propel the field forward. Highlighted in a recent article by KXAN, experts like Dr. Peter Stone and Justin Hart showcased their work, including advancements in generative AI, which is integral to tasks ranging from domestic chores to humanoid robot soccer, a part of the RoboCup Federation's ambitious goal of a robot team winning the World Cup by 2050.

03/14/2024 - An innovative approach uses artificial intelligence and biosensors to pave the way for faster drug development.

02/01/2024 - Researchers from The University of Texas at Austin and McGill University delve into the mathematical intricacies of wire puzzle design. Focusing on geometrical aspects, they establish criteria for puzzle characteristics, emphasizing the importance of a challenging experience. The team introduces quantitative metrics to assess tunnel-bubble structures, demonstrating their effectiveness in distinguishing puzzles from non-puzzles. Their findings provide a foundation for an optimization model, shaping the future of wire puzzle design.

01/25/2024 - The University of Texas at Austin is creating one of the most powerful artificial intelligence hubs in the academic world to lead in research and offer world-class AI infrastructure to a wide range of partners.

11/08/2023 - In mathematical optimization, a new approach is emerging, promising to transform how we tackle intricate challenges across various domains. Consider the complexity of bilevel optimization, a problem that has confounded experts in machine learning, engineering, and other fields. Recent advances are providing new insights into this intricate landscape, presenting a streamlined technique that has the potential to significantly enhance our ability to navigate these complex problems.

11/02/2023 - Smriti Singh spends a lot of time on social media. But, not in the way most students do.