Huangxing Hu
Papers
1
Total Citations
16
H-Index
1
About
Huangxing Hu is a leading researcher in structural health monitoring and intelligent robotics, with a focus on the safety assessment of large-span space structures. His work centers on developing efficient, deep learning-driven methods for detecting looseness in bolt-ball joints—a critical failure point in space frames that can cause catastrophic collapses. Hu’s major contribution is the creation of a lightweight, attention-enhanced neural network (CBAM-ResNet) that dramatically reduces computational complexity while maintaining high detection accuracy. This innovation enables real-time, robotic-assisted monitoring in practical engineering settings, overcoming the traditional trade-off between model performance and deployment efficiency. His most-cited paper, published in 2023, has already garnered 16 citations, reflecting its immediate impact on the field. By integrating advanced computer vision with cost-effective robotic platforms, Hu is paving the way for autonomous, continuous infrastructure inspection—a crucial step toward safer, smarter cities. His work bridges the gap between cutting-edge AI and real-world structural safety, making him a key figure in the future of intelligent maintenance systems.
Research Focus
Key Achievements
Top Papers
- 1