Refreshments are available starting at 10:45 a.m. The seminar will begin at 11 a.m.
Abstract
The broad agenda of Fei Miao’s work is to develop the foundations for the science of embodied AI—that is, to assure safety, efficiency, robustness, and security of AI systems by integrating learning, optimization, and control. Miao’s research interests span several technical fields, including multi-agent reinforcement learning, robust optimization, uncertainty quantification, control theory, and game theory. Application areas include connected and autonomous vehicles (CAVs), intelligent transportation systems and transportation decarbonization, smart cities, and power networks.
Miao’s research experience and current ongoing projects include robust reinforcement learning and control, uncertainty quantification for collaborative perception, game theoretical analysis for the benefit of information sharing for CAVs, data-driven robust optimization for efficient mobile cyber-physical systems (CPS), conflict resolution of smart cities, and resilient control of CPS under attacks. In addition to system modeling, theoretical analysis, and algorithmic design, Miao’s work involves experimental validation in real urban transportation data, simulators, and small-scale autonomous vehicles.
Speaker Biography
Fei Miao is a Pratt & Whitney Associate Professor in the School of Computing and courtesy faculty in the Department of Electrical and Computer Engineering at the University of Connecticut. She is also affiliated with the Pratt & Whitney Institute for Advanced Systems Engineering. Before joining UConn, Miao was a postdoctoral researcher in the General Robotics, Automation, Sensing, & Perception Lab and the Penn Research In Embedded Computing and Integrated Systems Engineering Center with George J. Pappas and Daniel D. Lee in the Department of Electrical and Systems Engineering at the University of Pennsylvania. Miao earned her PhD—as well as the Charles Hallac and Sarah Keil Wolf Award for the best doctoral dissertation—in electrical and systems engineering in 2016, along with a dual Master’s degree in statistics from the Wharton School at the University of Pennsylvania. She received her bachelor’s degree of science from Shanghai Jiao Tong University in 2010 with a major in automation and a minor in finance.