Center for Environmental Research and Technology

Join us for this engaging seminar to gain valuable insights into the future of autonomous driving. Dr. Qiu's research promises to revolutionize the way we perceive and address challenges in the realm of self-driving vehicles.

Event Details:

• Speaker: Dr. Hang Qiu
• Date: December 12, 2023
• Location: Room 105
• Time: 3:00 PM - 4:00 PM
• RSVP: All are welcome and encouraged to join! Light snacks and refreshments will be provided- if you are interested in attending, please RSVP here: https://forms.gle/L9XTeDwgyaxGDs6Z

About Dr. Hang Qiu: Dr. Hang Qiu is a faculty member of the Center for Robotics and Intelligent Systems (CRIS) and the Center for Environmental Research and Technology (CE-CERT) at UCR. Additionally, he is an Assistant Professor in the departments of Electrical and Computer Engineering (ECE) and Computer Science and Engineering (CSE) at UCR, where he leads the innovative Collaborative Intelligence Systems Lab (CISL). His pioneering research focuses on infusing collaborative intelligence into autonomous systems, bridging the gap between robot intelligence, edge/cloud intelligence, and human intelligence. Dr. Qiu's mission is to empower these systems to communicate and cooperate effectively, unlocking capabilities beyond individual capacities. Dr. Qiu earned his Ph.D. from the Networked Systems Lab at the University of Southern California and earned his bachelor's degree from the Internet of Things (IIOT) at Shanghai Jiao Tong University. Prior to his tenure at UCR, he contributed significantly to the field of autonomous driving as a software engineer at Waymo, Google's self-driving car spin-off. He also served as a postdoctoral scholar in the Platform Lab at Stanford University and collaborated with renowned organizations such as Microsoft Research, IBM Research, and General Motors.

Presentation Title: "Scene Understanding beyond the Visible"

Abstract: Recent years have seen tremendous iterations on autonomous driving technologies, pushing the deployment of self-driving cars closer to its realization. As the experimental deployments scale, more challenging and less frequent corner cases surface to stress- test the reliability of the autonomous driving system. Examples of these corner cases include limited visibility due to occlusion, degraded perception at long range, transient reflection and so on. To address the limited visibility issue, in particular, cooperative perception has been proposed to leverage vehicle-to-everything (V2X) communication to share perception data with nearby vehicles to fill in the invisible area. In this talk, Dr. Qiu will present a line of cooperative perception system research from its initial prototyping, scaling up, to its expansion from perception to end-to-end driving behaviors.