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Learning, Optimization and Control for Safety, Efficiency, and Security of Cyber-Physical Systems
Fei Miao
IRB 4105,Zoom Link: https://umd.zoom.us/j/94829400667?pwd=TkxHUGViQktxcW82L2pYRmNkMVZaUT09
Tuesday, February 14, 2023, 11:00 am-12:00 pm Calendar
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Ubiquitous sensing enables large-scale multi-source data of cyber-physical systems (CPS) collected in real-time and poses both challenges and opportunities for a paradigm-shift to AI-enabled CPS. Existing networked CPS decision-making frameworks lack understanding of the tridirectional relationship among communication, learning and control, let alone of how to define and quantify formally the benefits of information sharing. In this talk, we first present our research contributions on learning and control based on information sharing for CPS. We design a novel uncertainty quantification method for collaborative perception of connected autonomous vehicles (CAVs), and show the accuracy improvement and uncertainty reduction performance of our method. To utilize the information shared among agents, we then a safe and scalable deep multi-agent reinforcement learning (MARL) algorithms with truncated Q-function and safety guarantee based on continuous state space controller. To motivate agents to coordinate, we design a stable and efficient Shapley value-based reward reallocation for MARL. Considering system state uncertainties or even adversarial perturbations, we analyze what is the solution of MARL under state uncertainties and design robust algorithm to learn robust policies. We then briefly present our research contributions on data-driven robust optimization for efficient and climate friendly mobile CPS. Finally, we will highlight our research results on CPS security.


Fei Miao is an Assistant Professor of the Department of Computer Science & Engineering, a Courtesy Faculty of the Department of Electrical & Computer Engineering, University of Connecticut since 2017. She is also affiliated to the Institute of Advanced Systems Engineering and Eversource Energy Center. She was a postdoc researcher at the GRASP Lab and the PRECISE Lab of the University of Pennsylvania from 2016 to 2017. She received the Ph.D. degree and the Best Doctoral Dissertation Award in Electrical and Systems Engineering, with a dual M.S. degree in Statistics from the University of Pennsylvania in 2016. She received the B.S. degree in Automation from Shanghai Jiao Tong University. Her research focuses on reinforcement learning, robust optimization, uncertainty quantification, and game theory, to address safety, efficiency, robustness, and security challenges of cyber-physical systems.  Dr. Miao is a receipt of the NSF CAREER award and a couple of other awards from NSF, including awards from the Smart & Autonomous Systems, the Cyber-Physical Systems, and the Smart & Connected Communities programs. She received the Best Paper Award and Best Paper Award Finalist at the 12th and 6th ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS) in 2021 and 2015, respectively. 


This talk is organized by Richa Mathur