Liang Xiao
Papers
2
Total Citations
38
H-Index
2
About
Liang Xiao is a leading researcher at the intersection of reinforcement learning, network security, and wireless communications. Her work focuses on developing intelligent, adaptive systems that can operate safely in high-stakes environments. A key contribution is her pioneering research on safe exploration in reinforcement learning for network security, where she addresses the critical challenge of avoiding catastrophic failures—such as network outages or privacy breaches—during the learning process. This work, published in 2019, has garnered 20 citations and is foundational for deploying AI in safety-critical applications. She has also made significant strides in energy-efficient robotics, particularly in her 2021 study on reinforcement learning-based robot relays for unmanned aerial vehicles, which achieved 18 citations by enabling drones to resist smart jamming attacks while conserving power. Her research is notable for bridging theoretical advances in reinforcement learning with practical, real-world security and energy constraints. Liang Xiao’s work is essential reading for students and researchers interested in robust, secure, and efficient autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Reinforcement Learning with Safe Exploration for Network Security20 citations · 2019
- 2