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About

Hongyu Zhou is a researcher working at the intersection of control theory, robotics, and online optimization, with a particular focus on designing algorithms that perform reliably in uncertain, adversarial, and dynamic environments. His work addresses some of the most challenging problems in modern autonomy: how to coordinate multiple robots effectively when the future is unpredictable, and how to control complex systems safely when noise is non-stochastic and potentially adversarial. His most-cited contribution, "Online Submodular Coordination With Bounded Tracking Regret" (14 citations), establishes a rigorous theoretical foundation for multi-robot coordination in unstructured environments. Complementing this, his series of papers on safe non-stochastic control — spanning linear, nonlinear, and partially-observed systems — demonstrates a systematic effort to provide formal safety guarantees alongside performance optimality, accumulating over 20 citations collectively. His more recent work on simultaneous system identification and model predictive control pushes further toward practical autonomy, offering asymptotic convergence to optimal control without prior system knowledge. Across his portfolio, Zhou distinguishes himself through mathematically rigorous, algorithm-driven research that bridges theoretical guarantees with real-world robotic applications.