College of Natural Sciences | Point of Discovery
As the summer movie season kicks into high gear, we talk with a scientist about some of the challenges in simulating the way everyday objects behave on the big screen through computer generated imagery (CGI). Etienne Vouga's computer simulations have helped bring to life a wizard's hair in The Hobbit and clothing in Tangled.
With an advance that one cryptography expert called a "masterpiece," University of Texas at Austin computer scientists have developed a new method for producing truly random numbers, a breakthrough that could be used to encrypt data, make electronic voting more secure, conduct statistically significant polls and more accurately simulate complex systems such as Earth's climate.
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.
University of Texas researcher designs novel way to analyze bigger datasets using supercomputers and machine learning algorithms.
How do Netflix or Facebook know which movies you might like or who you might want to be friends with?
Here’s a hint: It starts with a few trillion data points and involves some complicated math and a lot of smart computer programming.
There are few things as full of anxiety, heartbreak, and anguish as finding out that you or someone you love has cancer. Unfortunately, it’s not at all uncommon. By the American Cancer Society’s estimates it is expected that in the year 2015 alone, there will be 1.6 million new cancer diagnoses and nearly 600,000 deaths—or roughly 1,600 people every day. But statistics are hardly necessary to realize the enormity of the problem. So far, the road to a cure has been long and complicated and with what’s seemed like no end in sight—until recently.
AUSTIN (KXAN) – A computer science professor at the University of Texas at Austin stopped by KXAN to talk about his research on computer gaming and the human brain. Dr. Risto Miikkulainen is studying the brain to figure out how it works and translate that knowledge to making better computer games.
A computer science team at The University of Texas at Austin has found that robots evolve more quickly and efficiently after a virtual mass extinction modeled after real-life disasters such as the one that killed off the dinosaurs. Beyond its implications for artificial intelligence, the research supports the idea that mass extinctions actually speed up evolution by unleashing new creativity in adaptations.