Peishan Huang

National University of Defense Technology

Papers

Total Citations

H-Index

About

Peishan Huang is a researcher advancing the intersection of formal methods and robotics through the lens of behavior trees. Her work focuses on the formal verification and synthesis of behavior trees, a key area in autonomous systems where correctness and reliability are paramount. In her most-cited paper, "Formal Verification Based Synthesis for Behavior Trees" (2023), Huang introduces a novel approach that integrates formal verification techniques directly into the synthesis process, ensuring that generated behavior trees satisfy critical safety and liveness properties from the outset. This contribution addresses a fundamental challenge in robotics and AI: how to automatically produce correct-by-construction control architectures. While her citation count is still growing—reflecting the recency and emerging nature of her work—the paper’s foundational methodology positions it as a potential cornerstone for future research in dependable autonomous systems. Huang’s research is particularly relevant for students and engineers working on robotic planning, human-robot interaction, and safety-critical software, offering a rigorous, mathematically grounded path to more trustworthy behavior generation.