Yuhan Li

National University of Defense Technology

Papers

Total Citations

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About

Yuhan Li is a researcher advancing the field of formal methods and software engineering, with a focus on the synthesis and verification of behavior trees—a key formalism in robotics, autonomous systems, and AI planning. Their most-cited work, "Formal Verification Based Synthesis for Behavior Trees" (2023), introduces a rigorous approach to automatically generating correct-by-construction behavior trees from formal specifications. This contribution bridges the gap between high-level task requirements and low-level execution, ensuring system reliability and safety without manual debugging. Though early in their career, Li’s work has already garnered attention, with this paper accumulating 2 citations—a promising start for a novel methodology. By integrating formal verification into the synthesis pipeline, Li addresses critical challenges in autonomous systems, where unverified behaviors can lead to failures. Their research holds potential for impact in robotics, cyber-physical systems, and human-robot interaction, offering a pathway to more trustworthy AI. As Li continues to develop these techniques, they are poised to become a key voice in formal methods and behavior engineering, inspiring students and researchers to explore the intersection of logic, synthesis, and real-world autonomy.