"Using Data for Increased Realism and Immersion with Haptic Modeling and Devices"
Thursday, November 17th @ 11am PST
CSE 2154 / Zoom - https://ucsd.zoom.us/j/92050012028
Speaker: Heather Culbertson
As technology advances, more of our daily lives are spent online and in front of screens. However, the digital interactions remain unsatisfying and limited, representing the human as having only two sensory inputs: visual and auditory. We have learned to adapt to using digital devices, communicating through keyboards, mice, and touchscreens, but these input methods are unnatural and provide limited information to the user. In this talk I will discuss our methods for creating more realistic and immersive virtual interactions using our unique approach that integrates design, mechatronics, and neuroscience. Our approach combines machine learning and data recorded from real-world interactions with objects with the goal of creating virtual objects that are indistinguishable from real life. This talk will cover the data-processing, algorithms, and hardware needed to model and render virtual objects and interactions for a variety of scenarios. I will also discuss current challenges and future directions in the field of haptics.
Heather Culbertson is a Gabilan Assistant Professor of Computer Science at the University of Southern California. Her research focuses on the design and control of haptic devices and rendering systems, human-robot interaction, and virtual reality. Particularly she is interested in creating haptic interactions that are natural and realistically mimic the touch sensations experienced during interactions with the physical world. Previously, she was a research scientist in the Department of Mechanical Engineering at Stanford University. She received her PhD in the Department of Mechanical Engineering and Applied Mechanics at the University of Pennsylvania in 2015. She is currently serving as Co-Chair for the IEEE Haptics Symposium. Her awards include the NSF CAREER Award, IEEE Technical Committee on Haptics Early Career Award, and Best Paper at UIST.