Tuesday, June 23, 2026
Ruikun Zhou, who recently completed the PhD program in Applied Math, received a Faculty of Mathematics Graduate Research Excellence Award for the paper, Resolvent-Type Data-Driven Learning of Generators for Unknown Continuous-Time Dynamical Systems, published with supervisor Prof. Jun Liu in IEEE Transactions on Automatic Control. This research develops a new data-driven framework for learning the fundamental operators that govern nonlinear dynamical systems directly from trajectory data, enabling model-based prediction, analysis, and control even for uncertain system.