Yiqing Yu
Papers
1
Total Citations
4
H-Index
1
About
Yiqing Yu is a researcher at the forefront of safe autonomy and stochastic control, with a focus on developing rigorous verification methods for safety-critical systems. Their most-cited work, "Safe Probabilistic Invariance Verification for Stochastic Discrete-Time Dynamical Systems" (2023, 4 citations), tackles the fundamental challenge of ensuring that robotic and control systems remain within safe operating regions over infinite time horizons, even when subject to random disturbances. This contribution is pivotal for applications ranging from autonomous driving to aerial robotics, where guaranteeing safety under uncertainty is paramount. By advancing set invariance theory for stochastic systems, Yu provides a formal framework that bridges probabilistic analysis and practical control design. Though early in their career, their work signals a deep commitment to the mathematical foundations of reliable autonomy, earning recognition from peers in the control and robotics communities. Yu’s research continues to push the boundaries of how we verify and trust intelligent systems operating in unpredictable environments.
Research Focus
Key Achievements
Top Papers
- 1