10/28/2020 -We live in an increasingly digital era. Research shows that the average American checks their phone about 58 times daily, and spends an average of 4.5 hours a day on their phone. Without a doubt the amount of time the modern-day person spends on their phones has changed many aspects of how our society functions. For example, in the past decade we have seen a dramatic shift in forms of advertising.Read more
10/06/2020 -A group of Texas Computer Science (TXCS) researchers from the Autonomous Mobile Robotics Laboratory (AMRL) comprising Joydeep Biswas, Sadegh Rabiee, Jarrett Holtz, Kavan Sikand, Max Svetlik, and John Bachman (UMass Amherst) have reached an incredible milestone in their research: deploying an autonomous robot that autonomously navigates on the campus-scale, resilient to everydRead more
08/26/2020 -The National Science Foundation has selected The University of Texas at Austin to lead NSF AI Institute for Foundations of Machine Learning, bolstering the university’s existing strengths in this emerging field. Machine learning is the technology that drives AI systems, enabling them to acquire knowledge and make predictions in complex environments. This technology has the potential to transform everything from transportation to entertainment to health care.Read more
07/17/2020 -Imagine that you are a robot in a hospital: composed of bolts and bits, running on code, and surrounded by humans. It’s your first day on the job, and your task is to help your new human teammates—the hospital’s employees—do their job more effectively and efficiently. Mainly, you’re fetching things. You’ve never met the employees before, and don’t know how they handle their tasks. How do you know when to ask for instructions? At what point does asking too many questions become disruptive?Read more
06/22/2020 -Story by Cason Hunwick for the College of Natural Science's News Page.
University of Texas at Austin computer science researcher Kristen Grauman was selected as a finalist for the 2020 Blavatnik National Awards for Young Scientists.Read more
03/25/2020 -The promise of artificial intelligence to solve problems in drug design, discover how babies learn language, and make progress in many other areas has been stymied by the inability of humans to understand what's going on inside AI systems.
Researchers at six universities, including The University of Texas at Austin, are launching a partnership aimed at turning these AI "black boxes" into human-interpretable computer code, allowing them to solve hitherto unsolvable problems.Read more