About Me

I am a Ph.D. candidate in the Department of Computer Science and Engineering at UC San Diego, advised by Professor Sicun Gao. My research lies at the intersection of reinforcement learning, control theory, and stability analysis, with a focus on developing practical algorithms for safe and reliable decision-making in complex systems. I hold a master’s degree in Applied Mathematics from National Tsing-Hua University, where I built a strong foundation in optimization and mathematical modeling. I am actively seeking a full-time research position to apply my expertise in developing effective and robust AI algorithms.

Research Interests

Reinforcement Learning, Safety Certificates in Robotics, Optimization, Control Theory.

Publications

Neural Lyapunov Control
Ya-Chien Chang, Nima Roohi, and Sicun Gao
NeurIPS (Conference on Neural Information Processing Systems) 2019
Stabilizing Neural Control Using Self-Learned Almost Lyapunov Critics
Ya-Chien Chang and Sicun Gao
ICRA (International Conference on Robotics and Automation) 2021
Learning Stabilization Control from Observations by Learning Lyapunov-like Proxy Models
Milan Ganai, Chiaki Hirayama, Ya-Chien Chang, and Sicun Gao
ICRA (International Conference on Robotics and Automation) 2023
Extremum-Seeking Action Selection for Accelerating Policy Optimization
Ya-Chien Chang, and Sicun Gao
ICRA (International Conference on Robotics and Automation) 2024