Xinghao Wang
Papers
1
Total Citations
10
H-Index
1
About
Xinghao Wang is a researcher at the forefront of non-destructive evaluation and terahertz (THz) sensing technologies, with a particular focus on advanced composite materials. His key research areas include the characterization of fiber-reinforced polymers, structural health monitoring, and the application of deep learning to electromagnetic wave analysis. Wang’s most notable contribution is the development of a Transformer-based neural network for automatic delamination detection in quartz fiber-reinforced polymer curved structures, utilizing improved time-domain spectroscopy (THz-TDS). This work, published in 2024 and already garnering 10 citations, demonstrates a novel integration of artificial intelligence with terahertz imaging to solve a critical challenge in aerospace and defense material inspection. By enabling automated, high-accuracy defect identification in complex geometries, Wang’s research significantly advances the reliability and efficiency of non-destructive testing. His work stands out for bridging the gap between cutting-edge machine learning architectures and practical industrial applications, offering a scalable solution for quality assurance in high-performance composites.
Research Focus
Key Achievements
Top Papers
- 1