Abstract

While driving to our favorite restaurant, we keep reacting to the changing traffic situations. For instance, we have to brake hard to avoid hitting those cut-in scooters. Humans constantly assess inherent risk and operate vehicles accordingly. What are the underlying computational principles? In this talk, I will share the efforts we are taking toward a human-like risk assessment framework. Our ultimate goal is to deploy our findings for next-generation intelligent driving systems toward a zero collision mobility experience.

Bio

Yi-Ting is an assistant professor in the Department of Computer Science at National Yang Ming Chiao Tung University. He received his Ph.D. degree from the Department of Electrical and Computer Engineering at Purdue University in 2015 and a B.S. degree in Electronics Engineering from National Chiao Tung University in 2009. He was a senior scientist at Honda Research Institute USA from 2015 to 2020. He was visiting researcher at Google ATAP working on mobile user authentication in Spring 2015. Before that, he was a computer vision researcher at the University of California at Merced in 2014. His research interests lie in computer vision, machine learning, robotics, and behavior science, and their applications to intelligent systems. (https://www.cs.nycu.edu.tw/members/detail/ychen)

All faculty and students are welcome to join.