Ruicong Xia
Papers
1
Total Citations
10
H-Index
1
About
Ruicong Xia is making significant strides in the non-destructive evaluation of advanced composite materials, with a primary focus on quartz fiber-reinforced polymer (QFRP) structures. Her key research areas encompass terahertz time-domain spectroscopy (THz-TDS), deep learning, and automated defect characterization. Xia’s most notable contribution is the development of a Transformer-based neural network that dramatically improves the automatic detection and characterization of delamination in curved QFRP components—a critical challenge in aerospace and defense applications. By integrating an improved THz-TDS signal processing pipeline with a state-of-the-art attention mechanism, her work enables precise, real-time identification of subsurface defects that traditional methods often miss. Her 2024 paper on this topic has already garnered 10 citations, reflecting its immediate impact on the field. This achievement not only advances the reliability of composite structural health monitoring but also paves the way for safer, more efficient manufacturing and maintenance of high-performance curved structures. Xia’s innovative fusion of terahertz imaging and transformer architectures positions her as a rising leader in intelligent materials characterization.
Research Focus
Key Achievements
Top Papers
- 1