Margaret Chapman

Margaret Chapman is an Assistant Professor in the Department of Electrical & Computer Engineering at the University of Toronto. Her research focuses on bridging the gap between robust and stochastic optimal control via risk measure theory, with emphasis on safety-critical applications in healthcare and sustainable cities. She is especially interested in developing risk-sensitive control methods that scale to high-dimensional systems while providing safety or quality-of-approximation guarantees by exploiting domain-specific structure, as well as safety analysis methods that rigorously integrate physics-based and data-driven models with non-asymptotic quality-of-approximation guarantees.

Margaret P. Chapman is an Assistant Professor at the University of Toronto, specializing in stochastic optimal control, risk analysis, and safety-critical systems with applications in cancer treatment. Her research explores risk-sensitive safety analysis, risk-averse control strategies, and the integration of risk measures such as conditional value-at-risk (CVaR) into dynamic systems. She investigates the use of optimal control in robotics, autonomous systems, and biomedical applications, including cancer treatment through switched dynamical systems and cyclic drug scheduling. Her work emphasizes the development of scalable risk analysis methods and safety verification techniques for stochastic systems.