Mao Yanbing
Papers
1
Total Citations
2
H-Index
1
About
Dr. Mao Yanbing is a pioneering researcher in the field of safety-critical cyber-physical systems (CPS), with a particular focus on runtime assurance and machine learning integration. His most notable contribution is the groundbreaking concept of the "Runtime Learning Machine," introduced in his 2025 paper, which has already garnered attention with 2 citations in its early stages. This work proposes a novel architecture comprising three interactive components: a high-performance (HP)-Student for efficient learning, a high-assurance (HA)-Teacher for safety verification, and a Coordinator to manage their interplay. Dr. Mao’s research addresses the critical challenge of deploying learning-enabled systems in environments where failures are unacceptable, such as autonomous vehicles and medical devices. By bridging the gap between high-performance AI and rigorous safety guarantees, his work offers a practical framework for trustworthy CPS. His contributions are particularly significant for students and researchers exploring runtime monitoring, formal verification, and adaptive systems. Dr. Mao’s innovative approach positions him as a rising thought leader in ensuring that intelligent systems can operate safely under real-world uncertainties.
Research Focus
Key Achievements
Top Papers
- 1Runtime Learning Machine2 citations · 2025