I am an Assistant Professor of Automotive Engineering at Clemson University International Center for Automotive Research (CU-ICAR) since 2018, directing AutoAI Lab research group.
My team is focusing on Autonomous AI research especially robotic Perception & Intelligence in interactive, dynamic, and uncertain environments, including topics such as sensing, visual perception/mapping, deep/machine learning, and artificial intelligence (AI) for robotics. We are also developing assistive and assistance technologies of navigation and safety aid to helping people with special needs.
Prior to joining Clemson, I earned a Ph.D. degree in Electrical Engineering at The City College (CCNY), The City University of New York (CUNY). I also had industrial R&D experiences at China Academy of Telecommunications Technology, IBM and HERE North America LLC that builds maps and location platform enabling self-driving vehicles.
My group is looking for motivated students! Please don’t hesitate to email me to apply if you are interested in.
View All Publications at: All Publications, or Google Scholar.
This course is designed to provide knowledge in the design and implementation of real-time parallel and high-performance computing (HPC), GPU computing, AI and edge-AI computing, autonomy stacks, and simulation technologies for autonomous robots and vehicle software systems. The students will achieve these learning objectives through extensive examples, homework, case and paper studies, and project design.
This course will introduce the fundamental technologies for autonomous vehicle sensors, perception, and machine learning, from electromagnetic spectrum characteristics and signal acquisition, vehicle extrospective sensor data analysis, perspective geometry models, image and point cloud processing, to machine/deep learning approaches. We will also have hands-on programming experience in vehicle perception problems through homework and class projects.