10/05/2020 - Source: College of Natural Sciences Many of the decisions we make are now guided by computational simulations, from designing new spacecraft to predicting the spread of a pandemic. But it's not enough for a simulation model to just issue predictions. A decision-maker needs to know just how much those predictions can be trusted.
08/31/2020 - A team comprising Texas Computer Science (TXCS) Ph.D. student Santhosh Ramakrishnan, postdoctoral researcher Ziad Al-Halah, and TXCS Professor Kristen Grauman recently won first place in the 2020 Habitat visual navigation challenge held at the Conference on Computer Vision and Pattern Recognition (CVPR).
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.
07/28/2020 - Texas Computer Science (TXCS) is proud to announce that two research teams have received awards at preeminent evolutionary computation conferences.
07/22/2020 - Original story by Marc G Airhart, College of Natural Sciences
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?
07/15/2020 - Article by Esther R Robards-Forbes | College of Natural Sciences
06/24/2020 - Note: the original article was written for and published on the Texas Advanced Computing Center website. Authorship credit goes to Faith Singer-Villalobos.
06/11/2020 - The datasets used by many software applications can be represented as graphs, defined by sets of vertices and edges. These graphs are rich with useful information, and can be used to determine patterns and relationships among the stored data. This process of discovering relevant patterns from graphs is called Graph Pattern Mining (GPM). A team of Texas Computer Science (TXCS) researchers advised by Dr. Keshav Pingali has done groundbreaking work to make GPM programs more efficient and accessible.
05/28/2020 - Artificial Intelligence (AI) is a rapidly evolving field, with advancements occurring every day. While the idea of an artificial intelligence system may conjure images of an autonomous machine that rattles out facts like a hi-tech encyclopedia, complex AI exists only because a countless number of talented individuals dedicate their time toward refining these systems.