## Bio

Hans Riess received a B.S. in pure mathematics from Duke University. In 2022, he received a Ph.D. in Electrical and Systems Engineering from the University of Pennsylvania where, with Robert Ghrist, he developed a novel approach of extracting global insights into complex systems using algebraic lattices and sheaves. Hans employs algebraic and topological methods to pioneer advancements in machine learning, autonomy, and optimization. He is currently a postdoctoral associate in the Autonomous Systems Lab directed by Michael M. Zavlanos at Duke University where he leads efforts in the development and analysis of networked autonomous systems.