Position:  PhD Candidate

Current Institution:  University of Southern California

Abstract:  Analysis, Design, and Optimization of Large-Scale Networks of Dynamical Systems

My research focuses on structure identification and optimal control of large-scale networks of dynamical systems. These systems are becoming increasingly important in science and engineering with applications ranging from economics, social networks, power systems, and robotics. Consequently, network science has emerged as an interdisciplinary field that draws from diverse disciplines, including graph theory, matrix theory, dynamical systems optimization, and statistical mechanics. Conventional optimal control of distributed systems relies on centralized implementation of control policies. In large systems, centralized information processing imposes a heavy burden on individual nodes and is often infeasible. To overcome this challenge, I combine tools and ideas from control theory, distributed optimization, and compressive sensing to develop distributed estimation and control strategies that require limited information exchange between the individual subsystems.

Bio:
Sepideh Hassan Moghaddam is currently pursuing her PhD degree in the Department of Electrical Engineering at the University of Southern California, Los Angeles. Her primary research interests are in optimal design analysis and optimization of distributed and large-scale networks. Sepideh received her Bachelor’s degree in Electrical Engineering from Sharif University of Technology Tehran Iran in 2013 and her Master’s degree in Electrical Engineering from University of Minnesota Twin Cities in 2016. She was the Gold Medalist of the Second National Astronomy Olympiad in 2006 and was the recipient of the four-year 3M Science and Technology Doctoral Fellowship in 2013.