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About

Hongchao Zhang is a researcher working at the intersection of control theory, cyber-physical systems (CPS) security, and machine learning, with a growing interest in advanced materials for human-machine interaction. His most influential work centers on applying Control Barrier Functions (CBFs) to guarantee safety in complex, real-world systems. His 2020 paper on CBFs for safe CPS under sensor faults and attacks (14 citations) established a rigorous framework for maintaining system safety even when adversarial inputs or hardware faults corrupt state estimation — a critical concern in domains like medical devices, autonomous transportation, and energy infrastructure. Building on this foundation, Zhang extended CBF methodologies into reinforcement learning environments, addressing the fundamental challenge of ensuring safety during exploration under uncertain dynamics, work that has garnered 9 citations. His 2022 study further strengthened robustness guarantees against both sensor and actuator failures in nonlinear systems. More recently, Zhang has ventured into materials science, contributing to zwitterionic hydrogel development for motion sensing and human-machine interfaces. Spanning formal verification, resilient control, safe RL, and smart materials, his research reflects a commitment to building reliable, intelligent systems across engineering disciplines.