Yuxing Li

University of Wollongong

Papers

1

Total Citations

102

H-Index

1

About

Yuxing Li is a leading researcher in advanced manufacturing, specializing in the integration of deep learning and in-situ monitoring for additive processes. Her primary focus lies in wire-arc additive manufacturing (WAAM), where she has pioneered vision-based melt pool monitoring techniques. Li's most-cited work, "Vision-based melt pool monitoring for wire-arc additive manufacturing using deep learning method" (2022, 102 citations), introduces a transformative approach that leverages convolutional neural networks to analyze high-speed camera images of the molten pool in real time. This contribution enables precise defect detection and process control, significantly improving the reliability and quality of WAAM components. By bridging computer vision and manufacturing science, Li has established a new paradigm for intelligent process optimization. Her research has profound implications for industries requiring large-scale, cost-effective metal part production, such as aerospace and automotive. With over 100 citations on her flagship paper alone, Li's work is widely recognized as foundational in the emerging field of AI-driven additive manufacturing. She continues to advance smart manufacturing systems, combining sensor fusion with machine learning to push the boundaries of automated production.

Research Focus

Key Achievements

1
H-Index
1
Papers
102
Total Citations
102
Avg Citations/Paper
🏆 Most Cited Paper
Vision-based melt pool monitoring for wire-arc additive manufacturing using deep learning method
102 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: University of Wollongong

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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