Wenquan Liu
Papers
1
Total Citations
10
H-Index
1
About
Wenquan Liu is a rising researcher in the field of non-destructive evaluation and structural health monitoring, with a particular focus on advanced composite materials. His work centers on the development of intelligent, data-driven methods for defect characterization, leveraging cutting-edge machine learning and terahertz time-domain spectroscopy (THz-TDS). Liu’s most notable contribution to date is the introduction of a Transformer-based neural network for the automatic detection and characterization of delamination in quartz fiber-reinforced polymer curved structures. This work, published in 2024, has already garnered 10 citations, signaling its immediate impact and relevance in the aerospace and advanced manufacturing communities. By integrating deep learning with THz-TDS, Liu has addressed a critical challenge in inspecting complex geometries, moving beyond traditional signal processing toward automated, high-accuracy diagnostics. His research bridges the gap between materials science and artificial intelligence, offering practical solutions for quality control in high-performance composites. As an emerging voice in his field, Wenquan Liu is poised to make further contributions to smart sensing and intelligent infrastructure, with his early work already laying a strong foundation for future innovation.
Research Focus
Key Achievements
Top Papers
- 1