Academic Staff

Brief Biosketch

Dr. Runsheng Li is currently a Research Assistant Professor in the Department of Industrial and Systems Engineering at The Hong Kong Polytechnic University. Before this, he was a lecturer at the China University of Petroleum, and a postdoctoral research fellow in the Aviation Service Research Centre (PolyU-Boeing joint lab). He received his Ph.D. in School of Mechanical Science and Engineering from Huazhong University of Science and Technology in 2022 (Direct-entry PhD). His research interests include Additive Manufacturing, AI+Manufacturing, and Space and Aviation Manufacturing, He has established a partnership with Boeing, Airbus, COMAC, AVIC and CASC. 

As of January 2026, he has undertaken over 10 projects as PI or Co-PI, including Civil Aircraft Special Projects, the National Key Research and Development Program, the Shenzhen-Hong Kong-Macau Technology Research Programme (Type C), and the Innovation and Technology Support Programme (Platform & Collaborative). He has published more than 20 papers as the first author or corresponding author, been granted 15 invention patents, authored one monograph, and contributed to nine Chinese national standards.

Research Interests

• Additive Manufacturing
• AI+Manufacturing
• Space and Aviation Manufacturing

Selected Publications

1. Du Y. ^#,*, Tuhin M., Li R.*, …, Tarasankar D.*. Deep learning applications for enhancing process, structure, and properties in additive manufacturing. Progress in Materials Science. 2025, 101587
2. Tan C.^#, Li R.^#, Su J., et al. Review on field assisted metal additive manufacturing. International Journal of Machine Tools and Manufacture, 2023.104032. (ESI Highly Cited Papers/hot Papers)
3. Lin H. ^#, Fu M., …, Li R.*. Ultrasonic rolling-assisted additive manufacturing; IN718 superalloy; grain refinement; Mechanical properties enhancement; Dislocation strengthening. Additive Manufacturing, 2025, 104891 (ESI Highly Cited Papers/hot Papers
4. Lu Y. ^#, Zhang M., … Li R.*, et al. Microstructures, heat treatments and mechanical properties of AerMet100 steel fabricated by wire arc additive manufacturing with micro rolling. Additive Manufacturing, 2022, 56: 102885
5. Li R.^#, Wang G., Zhao X., et al. Effect of path strategy on residual stress and distortion in laser and cold metal transfer hybrid additive manufacturing. Additive Manufacturing, 2021, 46: 102203.
6. Li R.^#, Wang G., Ding Y., et al. Optimization of the geometry for the end lateral extension path strategy to fabricate intersections using laser and cold metal transfer hybrid additive manufacturing. Additive Manufacturing, 2020, 36:101546
7. Li W. ^#, Zhang H., … Li R.*. Deep learning based online metallic surface defect detection method for wire and arc additive manufacturing. Robotics and Computer-Integrated Manufacturing. 2023, 80: 102470 (ESI Highly Cited Papers)
8. Li R.^#, Ju G., Zhang Y., et al. Simulation of residual stress and distortion evolution in dual-robot collaborative wire-arc additive manufactured Al-Cu alloys. Virtual and Physical Prototyping, 2024. (ESI Highly Cited Papers/hot Papers)
9. Li R.^#, Ma H., Xie R., et al. Application of unsupervised learning methods based on video data for real time anomaly detection in wire arc additive manufacturing. Journal of Manufacturing Process, 2025, 143, 37-55 (ESI Highly Cited Papers/hot Papers)