Hai Zhong

Papers

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About

Hai Zhong is a researcher whose work lies at the intersection of multi-robot planning, stochastic control, and safe autonomy. His primary research focuses on developing tractable algorithms for constrained stochastic games, where multiple agents must coordinate under uncertainty while respecting critical safety constraints. Zhong's most-cited paper, "Chance-Constrained Iterative Linear-Quadratic Stochastic Games" (2022), introduces a novel framework that reformulates chance-constrained stochastic games into a computationally efficient iterative linear-quadratic structure. This contribution directly addresses a fundamental challenge in robotics: enabling teams of autonomous systems to operate safely in unpredictable environments without sacrificing performance. By bridging game theory with chance-constrained optimization, his work provides a principled approach to guarantee probabilistic safety in multi-agent interactions. While his citation count is still growing, the methodological rigor and practical relevance of his research have already established him as an emerging voice in the field. Zhong's contributions are particularly valuable for applications in autonomous driving, drone swarms, and collaborative manipulation, where real-time safety assurance under uncertainty remains an open frontier.