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MMAE Seminar - Dr. Shuo Han - Systematic Design of Decentralized Algorithms for Consensus Optimization

Event Date 

May 1, 2019 - 3:30pm to 4:30pm

Location 

John T. Rettaliata Engineering Center
Room 104
10 West 32nd Street
Chicago, IL 60616

Description 

Armour College of Engineering's Mechanical, Materials, and Aerospace Engineering Department will welcome Dr. Shuo Han, Assistant Professor in the Department of Electrical and Computer Engineering at the University of Illinois at Chicago, on Wednesday, May 1st, to present his lecture, Systematic Design of Decentralized Algorithms for Consensus Optimization.

Abstract

Decentralized optimization algorithms are widely used in the control of networked cyber-physical systems such as the power grid, transportation networks, and multi-robot teams. In a decentralized algorithm, the nodes (agents) collectively solve an optimization problem by solving part of the problem locally and exchanging messages over a communication network. In this talk, I will present a systematic procedure for designing decentralized optimization algorithms for a special class of problems in which the objective function is a sum of local objective functions. Specifically, I will show that a decentralized optimization algorithm can be synthesized by combining an existing base optimization algorithm (e.g., gradient descent) and a consensus tracking algorithm. A major benefit of this procedure is that one can separately choose the base optimization algorithm to accommodate different types of objective functions and the consensus tracking algorithm to accommodate different types of communication networks. In addition, parameters used in the synthesized algorithm can be selected in an automated manner by numerically computing a certificate of convergence using tools from robust control theory.

Biography

Dr. Shuo Han is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Illinois at Chicago. Previously, he was a postdoctoral researcher in the Department of Electrical and Systems Engineering at the University of Pennsylvania. He received his B.E. and M.E. in Electronic Engineering from Tsinghua University in 2003 and 2006, and his Ph.D. in Electrical Engineering from the California Institute of Technology in 2014. His research interests lie broadly in the areas of optimization and control theory with applications in large-scale interconnected cyber-physical systems such as transportation networks and the power grid.

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