Jingyi Huang
Papers
1
Total Citations
7
H-Index
1
About
Jingyi Huang is an emerging researcher whose work sits at the intersection of intelligent control systems, multi-agent robotics, and cybersecurity-aware automation. Their research focuses on developing advanced control strategies for multi-robot systems, with a particular emphasis on resilience against adversarial conditions. In their most notable contribution, Huang introduces a neural-network-based framework for achieving specified-time formation maneuver control in second-order nonlinear multi-robot systems, specifically addressing the critical challenge of False Data Injection (FDI) attacks — a growing concern in networked robotic and cyber-physical systems. This work demonstrates Huang's ability to bridge sophisticated mathematical control theory with practical, real-world security threats, offering solutions that are both theoretically rigorous and implementationally relevant. Published in 2025 and already accumulating citations, this research signals a promising trajectory in a field where autonomous systems must operate reliably under adversarial interference. Huang's contributions are particularly timely as industries increasingly deploy collaborative robot systems in environments vulnerable to cyberattacks, making resilient, intelligent control design an essential frontier of modern robotics research.
Research Focus
Key Achievements
Top Papers
- 1