Academic Staff

Brief Biosketch

Dr Su obtained a PhD degree from The University of Hong Kong, an MSc degree from Xi’an Jiaotong University, and a B.Eng degree from Jilin University in 2025, 2021 and 2018, respectively. Prior to joining the ISE Department, he worked as a Post doctoral Fellow in the Department of Data and Systems Engineering at HKU. His research interests include digital twins, industrial artificial intelligence, logistics optimization, smart manufacturing, and reverse supply chain management. He has published numerous papers in leading international journals, including AiC, ADVEI, CIE, and IEEE TASE, etc. His research has received multiple recognitions, such as the 1st Prize Best Conference Paper Award at NSFC RGC 2025, 1st Prize Best Poster Award at IPIC 2025, Best Digital Twin Thesis Award at DTIC 2026, and Best Application Paper Award Finalist at IEEE CASE 2023, etc. He undertakes academic services as a guest editor and conference session chair in various leading journals and international conferences.

Research Interests

Ddigital twins, industrial artificial intelligence, logistics optimization, smart manufacturing, and reverse supply chain management. 

Selected Journal Publications

1. Su, S., Yu, C., Jiang, Y., Kang, K., & Zhong, R. Y.* (2023). Trading building demolition waste via digital twins. Automation in Construction, 156, 105105.
2. Su, S.*, Zhong, R. Y., Jiang, Y., Song, J., Fu, Y., & Cao, H. (2023). Digital twin and its potential applications in construction industry: State-of-art review and a conceptual framework. Advanced Engineering Informatics, 57, 102030.
3. Su, S., Yu, C., Jiang, Y., & Zhong, R. Y.* (2025). Digital Twin-enabled Building Demolition Waste Trading: A Demonstrative Case. IEEE Transactions on Automation Science and Engineering, 1-1.
4. Su, S., Yang, Y., Besklubova, S., Song, J., Kong, X. T. R., & Zhong, R. Y.* (2026). Digital Twin-Enabled Reverse Supply Chain for Building Demolition Waste Management. Computers & Industrial Engineering, 211, 111605.
5. Su, S., Cao, H.*, & Zhang, Y. (2021). Dynamic modeling and characteristics analysis of cylindrical roller bearing with the surface texture on raceways. Mechanical Systems and Signal Processing, 158, 13, 107709.
6. Su, S., Zhong, R. Y.*, & Jiang, Y. (2022). Digital twin and its applications in the construction industry: A state-of-art systematic review. Digital Twin.
7. Cao, H.*, Su, S., Jing, X., & Li, D. (2020). Vibration mechanism analysis for cylindrical roller bearings with single/multi defects and compound faults. Mechanical Systems and Signal Processing, 144, 26, 106903.
8. Jiang, Y., Su, S., Zhao, S., Zhong, R. Y.*, Qiu, W., Skibniewski, M. J., Brilakis, I., & Huang, G. Q. (2024). Digital twin-enabled synchronized construction management: A roadmap from construction 4.0 towards future prospect. Developments in the Built Environment, 19, 100512.
9. Yin, L., Cheng, M., Su, S., Zhong, R. Y.*, & Zhao, S. (2025). An explainable super-resolution visual method for micro-crack image detection. Pattern Recognition Letters, 189, 157-165.
10. Liu, J., Cao, H.*, Su, S., & Chen, X. (2023). Simulation-Driven Subdomain Adaptation Network for bearing fault diagnosis with missing samples. Engineering Applications of Artificial Intelligence, 123, 106201.