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About

Jinsun Liu is a robotics and autonomous systems researcher whose work spans safe motion planning, reachability-based control design, and bipedal locomotion. His research addresses one of the most pressing challenges in modern robotics: enabling autonomous systems to operate safely and efficiently in real time, even under uncertainty and complex dynamics. Liu's foundational contribution in bipedal robot control leverages template-anchor frameworks to bridge the gap between simplified reduced-order models and high-fidelity full-order representations, enabling safe online gait design — a paper that has garnered 10 citations. His REFINE framework, developed across multiple iterations, applies robust feedback linearization and zonotope-based reachability analysis to provide provable safety guarantees for autonomous vehicle motion planning without sacrificing computational tractability, accumulating 10 combined citations. His RADIUS framework further advances the field by incorporating risk-awareness into real-time reachability-based planning, moving beyond overly conservative deterministic approaches through chance-constrained optimization. Collectively, Liu's work represents a meaningful push toward deploying autonomous systems — from legged robots to self-driving vehicles — that are both theoretically rigorous and practically viable, making his research highly relevant to students and engineers working at the intersection of control theory, robotics, and autonomous systems.