Dongke Zhao
Papers
1
Total Citations
19
H-Index
1
About
Dongke Zhao is a rising researcher in the field of cyber-physical systems and control theory, with a focus on resilient and secure networked control architectures. His work addresses critical challenges at the intersection of adaptive neural networks, event-triggered control, and cybersecurity. In his most-cited paper, "Resilient event-triggering adaptive neural network control for networked systems under mixed cyber attacks" (2024, 19 citations), Zhao proposes a novel framework that maintains system stability and performance despite simultaneous deception and denial-of-service attacks. This contribution is particularly significant for safety-critical applications such as autonomous vehicles and industrial automation, where communication constraints and adversarial threats are prevalent. By integrating event-triggered mechanisms with adaptive neural network compensation, Zhao’s approach reduces unnecessary data transmission while ensuring robust fault tolerance. Though early in his career, his work has already garnered attention for its practical relevance and theoretical rigor. Zhao’s research promises to advance the design of intelligent, attack-resilient control systems, positioning him as a promising voice in the next generation of control engineers tackling real-world security and efficiency challenges.
Research Focus
Key Achievements
Top Papers
- 1