Kai S. Yun

Kai Yun is a graduate student in mechanical engineering whose work addresses fundamental safety challenges for autonomous robots. His research bridges the critical gap between rigorous theoretical guarantees and real-world deployment. By integrating control theory, deep learning, and large foundation models, he develops scalable control architectures for complex, high-dimensional systems, including quadruped and humanoid robots. He developed a framework for provably safe and scalable reinforcement learning, ensuring strict constraint satisfaction in high-dimensional systems. He also tackles uncertainties in system dynamics and perception modules to maintain reliability under out-of-distribution scenarios. Kai uses optimization methods and semidefinite programming to synthesize and verify these control architectures. As a MathWorks Fellow, Kai will scale formal synthesis of safe controllers to highly dynamic humanoid systems and develop neural-control integration frameworks, bringing theoretical safety guarantees closer to practical use in autonomous robots.