Ding Zhao is an assistant professor of Mechanical Engineering. He is also associated with the Robotics Institute and the Machine Learning Department at the School of Computer Science and the Wilton E. Scott Institute for Energy Innovation. Directing the Safe AI Laboratory, Zhao aims to develop verifiable, affordable, and good-for-all learning for robotics in the face of the uncertain, dynamic, time-varying, multiple agents, and possibly human-involved environment by bridging statistics and cybernetics.
Zhao is recognized nationally and internationally for his research on autonomous/connected vehicles and smart cities, which synthesizes methods in machine learning, robotics, and design. His group develops rigorous test methods to verify AI-powered robots and learning/generative approaches that model the operational environment with big data to support vision and decision-making development. Methods and tools developed by the lab are being used by the industry and regulation institutes.
Zhao’s research has been granted funding by the National Science Foundation, Department of Transportation, and Department of Energy. He also works with leading self-driving companies around the world including Uber, Toyota, and Bosch.
Making AI Safer for Autonomous Vehicles
2016 Ph.D., Mechanical Engineering, University of Michigan
2010 BS, Automotive Engineering, Jilin University
Building safer AI for a better future
Leading the Safe AI Lab, Assistant Professor of Mechanical Engineering Ding Zhao is spearheading research to develop safe, transparent, and reliable AI for autonomous vehicles.