Ziyun (Claude) Wang is an assistant professor in the Department of Electrical and Computer Engineering. His research focuses on enabling intelligent robotic systems capable of perceiving, understanding, and interacting with complex and dynamic environments. He is broadly interested in embodied AI and how robots can operate reliably under extreme or unstructured conditions, such as high-speed motion, challenging lighting, or rapidly changing scenes. His work spans the development of geometric and learning-based methods for motion and scene understanding, as well as robust perception and control strategies that bridge theory and real-world deployment.
A key element of his research is leveraging emerging sensing technologies, particularly neuromorphic sensors, as powerful tools for robotic perception. By exploiting the high temporal resolution and sparse data characteristics of event-based sensors, Dr. Wang designs algorithms for fast and efficient scene understanding, enabling capabilities in high-speed vision and low-latency motion estimation under difficult visual conditions. He has co-authored publications in leading venues including CVPR, ICCV, ECCV, ICLR, AAAI, ICIP, ICCP, ISER, and RA L. He obtained his PhD from the GRASP Laboratory at the University of Pennsylvania, advised by Prof. Kostas Daniilidis, and holds a bachelor’s degree in Computer Science from Rice University and a master’s degree in Robotics from Penn.