Liangxiu Han
Papers
2
Total Citations
5
H-Index
2
About
Liangxiu Han is a leading researcher at the intersection of cybersecurity, robotics, and energy-efficient computer vision. Her work addresses critical challenges in securing human-robot interaction, particularly through the lens of digital twin systems. In her highly cited 2022 paper, she demonstrated how digital twins of robotic systems can be attacked to compromise both security and safety, revealing the intertwined vulnerabilities that arise in autonomous and collaborative manufacturing environments. This work has garnered 3 citations and is foundational for researchers developing resilient cyber-physical systems. More recently, Han has pioneered novel approaches to depth estimation using event cameras, which offer low latency and high dynamic range for applications in autonomous navigation and augmented reality. Her 2025 paper introduces a spike transformer network that leverages cross-modality knowledge distillation to achieve energy-efficient depth estimation, a breakthrough for resource-constrained robotic platforms. With 2 citations already, this work positions her at the forefront of neuromorphic vision and sustainable AI. Han’s contributions are shaping safer, smarter, and more efficient robotic systems, making her a key voice in the future of embodied intelligence.
Research Focus
Key Achievements
Top Papers
- 1
- 2