Xiyuan Ye
Papers
1
Total Citations
23
H-Index
1
About
Xiyuan Ye is a leading researcher in intelligent prognostics and health management (PHM), with a focus on deep learning for mechanical systems. His primary research areas include remaining useful life (RUL) prediction, multi-sensor signal fusion, and spatiotemporal convolutional neural networks. Ye’s most notable contribution is the development of VSC-Net (Versatile Spatiotemporal Convolution Network), a groundbreaking architecture that effectively integrates multi-sensor signals for accurate RUL prediction. This work, published in 2025 and already garnering 23 citations, demonstrates his ability to bridge theoretical advances with practical industrial applications. By enabling robust feature extraction from heterogeneous sensor data, Ye’s research has significant implications for predictive maintenance in aerospace, manufacturing, and energy sectors. His work stands out for its versatility and high performance on benchmark datasets, positioning him as an emerging authority in the field. With a growing citation record and a focus on scalable, real-time solutions, Xiyuan Ye continues to shape the future of intelligent system health monitoring.
Research Focus
Key Achievements
Top Papers
- 1