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  • CS Colloquium: Fei Miao (University of Connecticut) - Learning, Optimization and Control for Efficiency and Security of Cyber-Physical Systems

    Tue, Mar 08, 2022 @ 11:00 AM - 12:00 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars

    Speaker: Fei Miao, University of Connecticut

    Talk Title: Learning, Optimization and Control for Efficiency and Security of Cyber-Physical Systems

    Series: CS Colloquium

    Abstract: 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 data-driven CPS. For instance, how to capture the complexity and analyze the dynamical state information from data, and make decisions to improve safety, efficiency and security of the networked CPS is still challenging. In this talk, we present our research that integrates optimization, machine learning, control, and game theory to address these challenges, including theoretical contributions, algorithmic design, and experimental validations. We first present data-driven distributionally robust optimization (DRO) methods for CPS efficiency, with application on smart city resource allocation. We design algorithms to construct the uncertainty sets of the model prediction based on spatial temporal data. We prove the computationally tractable forms or equivalent convex optimization forms of the DRO problems to guarantee the worst-case expected cost of real-time decisions. We show the improvement of autonomous mobility-on-demand (AMoD) service fairness and efficiency based on large-scale dataset. Second, we summarize our research contribution for CPS security. We mainly present a hybrid state stochastic game model to guarantee the worst-case cost of the system, and a proved suboptimal algorithm to calculate the mixed policies. Finally, based on our active awarded projects, we briefly discuss future research directions on robust multi-agent reinforcement learning and data-driven robust optimization based decision-making, to address CPS safety, efficiency, and security challenges.

    This lecture satisfies requirements for CSCI 591: Research Colloquium

    Biography: 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. Her research interests lie in the optimization, machine learning, control, and game theory, to address safety, efficiency, and security challenges of cyber-physical systems. She received the Ph.D. degree and the Best Doctoral Dissertation Award in Electrical and Systems Engineering from the University of Pennsylvania in 2016. She received the B.S. degree majoring in Automation from Shanghai Jiao Tong University. She was a postdoc researcher at the GRASP Lab and the PRECISE Lab of Upenn from 2016 to 2017. Dr. Miao is a receipt of the NSF CAREER Award, the title of the project is \"Distributionally Robust Learning, Control, and Benefits Analysis of Information Sharing for Connected and Autonomous Vehicles\". Dr. Miao has also received 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 Best Paper Award and Best Paper Award Finalist at the ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS) in 2021 and 2015, respectively.

    Host: Jyo Deshmukh

    Location: 132

    Audiences: By invitation only.

    Contact: Assistant to CS chair


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