Time
Friday, 10/13/23 at 12:30 PM - 1:00 PM (Central)
Title
Designing Adaptive and Context-aware AR/VR Interactions
Abstract
Anyone who has witnessed the adoption of the Internet remembers the static and non-context-aware websites of the past. Compare that with the powerful engines behind the websites of today. These context-aware engines are equipped with machine learning and optimization algorithms that allow them to adapt and cater to their user's behavior and environment. This deep understanding of the user and their needs created a more personalized and efficient experience. Current AR/VR systems are not quite as static as the websites of yesteryear but still a long way to go from becoming as powerful and context-aware as browsing the web today. Rawan aspires to facilitate the road to achieving context-aware AR/VR systems that elegantly adapt their interactions to their user's behavior and environment. Rawan will discuss her work in AR/VR adaptive navigation aids, VR environment design via visual attention, and in-situ mobile AR content-authoring via 2D to 3D curve projection.
Bio
Rawan Alghofaili is an Assistant Professor of Computer Science at the University of Texas at Dallas. She received her Ph.D. in Computer Science under the mentorship of Professor Craig (Lap-Fai) from George Mason University where she was awarded the Distinguished Academic Achievement award. She received an M.S. from the University of Massachusetts-Boston in 2018 and an MEng. from Cornell University in 2014. Rawan was a research intern with Adobe's Creative Intelligence lab in the Summer of 2020 and a research intern with Meta Reality Labs in the Summer and Fall of 2021. Her work focuses on creating human-centered interactive AR/VR/MR systems which involves blending the wonderful worlds of AI, Computer Graphics, and HCI.