Zhaodan Kong

Zhaodan Kong is an Associate Professor in the Department of Mechanical and Aerospace Engineering at the University of California, Davis. He leads the Cyber-Human-Physical Systems Lab, focusing on interdisciplinary research at the intersection of control theory, machine learning, and formal methods. His work applies these techniques to autonomous systems, human-autonomy teaming, cyber-physical systems, and neural engineering. His research emphasizes interpretable and safe systems, with applications in robotics, healthcare, and environmental monitoring.

Research interests include control theory, machine learning, formal methods, and their applications to autonomous systems. Recent efforts explore energy-efficient UAV trajectory optimization, human-AI collaboration frameworks, and fault diagnosis in cyber-physical systems. His lab develops frameworks for cohort explanation in machine learning models and studies trust dynamics in human-autonomy interactions.

Publications span topics such as UAV mission planning, neural dynamics modeling, and interpretable AI. His work bridges theoretical foundations with practical applications, aiming to advance autonomous systems' reliability and human-system integration. Office hours are held during Winter 2025, indicating active academic engagement.