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CESG Seminar: “Sequential Learning, Optimization and Control for Cyber-Physical Systems” – Dileep Kalathil

November 17, 2017 @ 4:10 pm - 5:10 pm


“Sequential Learning, Optimization and Control for Cyber-Physical Systems”

Dr. Dileep Kalathil, ECE Assistant Professor, Texas A&M University



Convergence of the dramatic increase in available data and processing power, enabled by ubiquitous sensing and computing capabilities, is rapidly changing engineered systems. Cyber-Physical Systems (CPS) refers to such systems with tightly integrated computational, control and physical capabilities, like power grids and transportation networks. However, designing and implementing CPS involves an array of complex and challenging tasks: learning and making inference from data, designing scalable optimization and control methods, as well as developing decentralized and adaptive decision making algorithms.

In the first part of the talk, I will discuss a strategy for sequential learning and decision-making for decentralized CPS. I will first introduce a multi-player, multi-armed bandit’s framework for modeling this class of problems. I will then present a sequential learning and decision making algorithm to solve this problem and show that it achieves optimal performance.

In the second part of the talk, I will discuss an approach for simulation-based optimization and control of Markov Decision Process (MDP) models in the context of CPS. Designing exact optimization and control of such systems may be intractable due to its complexity. I develop a class of algorithms called Empirical Dynamic Programming to overcome this difficulty and provide provable non-asymptotic performance guarantees. I will also briefly discuss my work on data-driven learning and control in the context of transportation CPS.



Dr. Dileep Kalathil is an Assistant Professor in the Electrical and Computer Engineering Department at TAMU. Before joining TAMU, he was a postdoctoral scholar in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He received his PhD from the University of Southern California (USC) in 2014 where he won the best PhD Dissertation Prize in the USC Department of Electrical Engineering. He received an M.Tech from IIT Madras where he won the award for the best academic performance in the EE department. His research interests include control theory, sequential learning, game theory, and sustainable energy systems.


November 17, 2017
4:10 pm - 5:10 pm


WEB, Room 236-C
Wisenbaker Engineering Building


I-Hong Hou