Lu Shi

About me 

I am a robotics researcher with nearly a decade of experience in robotics control systems, spanning from classical methods such as PID and model-based control to advanced intelligent control frameworks, including reinforcement learning (RL), model predictive control (MPC), and vision-language-action (VLA) models. My work bridges theory and practice across diverse robotic platforms, spans locomotion (quadrupeds, wheeled-leg robots, mobile platforms), manipulation (robotic arms, dexterous hands), aerial robots, and soft robots. During my Ph.D., I focused on combining model-based and data-driven approaches through operator-based control (Koopman Operator Theory). As a postdoctoral researcher, my primary work centers on building generalized Real-to-Sim-to-Real (RSR) pipelines, integrating world models, and advancing embodied AI systems capable of robust adaptation across tasks and environments.

I am currently a postdoctoral researcher at the Institute of AI Industry Research, Tsinghua University. Before joining Tsinghua, I obtained my degree of Ph.D. in the Department of Electrical and Computer Engineering at the University of California, Riverside (UCR). I completed my bachelor’s degree in Automation and Control at Xi’an Jiaotong University, Xi'an.