Academic Staff

Brief Biosketch

Dr TSANG Yung Po (Paul) is currently a Lecturer in the Department of Industrial and Systems Engineering (ISE), The Hong Kong Polytechnic University. He received Ph.D. degree from the Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University in 2020. Prior to joining the Department of ISE, he worked as a Postdoctoral Fellow in the Laboratory of Artificial Intelligence in Design at Hong Kong Science Park, Hong Kong from October 2020. Also, he was awarded the Outstanding Paper Award in the IEEE International Conference on Industrial Engineering and Engineering Management in 2023, and the Highly Commented Award and Outstanding Paper Awards of Emerald Literati Network Awards in 2019.

Research Specialties

• Data-driven and human-centered decision-making
• Blockchain, Internet of Things, and Industry 4.0 technologies
• Cold chain and e-commerce logistics management

Professional Services

• Chairman of Cold Chain Committee & Council Member of Hong Kong Logistics Association (from 2023 to present)
• Panel Member of Cold Chain Logistics Professional (CCLP) accreditation of Hong Kong Logistics Association (Jan 2022 - Jan 2025)

Selected Journal Publications

• Tsang, Y. P., Fan, Y., Feng, Z. P., & Li, Y. (2024). Examining supply chain vulnerability via an analysis of ESG-Prioritized firms amid the Russian-Ukrainian conflict. Journal of Cleaner Production, 434, Article 139754. https://doi.org/10.1016/j.jclepro.2023.139754

• Liu, H., Tsang, Y. P., & Lee, C. K. M. (2024). A cyber-physical social system for autonomous drone trajectory planning in last-mile superchilling delivery. Transportation Research Part C: Emerging Technologies, 158, Article 104448. https://doi.org/10.1016/j.trc.2023.104448

• Li, Y.L., Tsang, Y. P., Wu, C. H., & Lee, C. K. M. (2024).  A Multi-Agent Digital Twin–Enabled Decision Support System for Sustainable and Resilient Supplier Management. Computers & Industrial Engineering, 187, Article 109838. https://doi.org/10.1016/j.cie.2023.109838

• Yang, T.T., Tsang, Y. P., Wu, C. H., Chung, K. T., Lee, C. K. M., & Yuen, S. S. M. (2023). Mixed reality‑based online 3D pallet loading problem to achieve augmented intelligence in e‑fulfilment processes. Operations Management Research. https://doi.org/10.1007/s12063-023-00432-6

• Mo, D. Y., Tsang, Y. P., Wang, Y., & Xu, W. (2023). Online reinforcement learning-based inventory control for intelligent E-Fulfilment dealing with nonstationary demand. Enterprise Information Systems, Article 2284427. https://doi.org/10.1080/17517575.2023.2284427

• Tsang, Y. P., Wu, C. H., & Dong, N. (2023). A Federated-ANFIS for Collaborative Intrusion Detection in Securing Decentralized Autonomous Organizations. IEEE Transactions on Engineering Management. https://doi.org/10.1109/TEM.2023.3304409

• Tsang, Y. P., Wu, C. H., Ip, W. H., & Lee, C. K. M. (2022). Federated-Learning-based Decision Support for Industrial Internet of Things (IIoT)-based Printed Circuit Board Assembly Process. Journal of Grid Computing, 20, Article 43. https://doi.org/10.1007/s10723-022-09637-8

• Tsang, Y. P., Wu, C. H., Ip, W. H., & Shiau, W. L. (2021). Exploring the intellectual cores of the blockchain–Internet of Things (BIoT). Journal of Enterprise Information Management. 34(5), 1287-1317.

• Tsang, Y. P., Wu, C. H., Lam, H. Y., Choy, K. L., & Ho, G. T. (2021). Integrating Internet of Things and multi-temperature delivery planning for perishable food E-commerce logistics: a model and application. International Journal of Production Research, 59(5), 1534-1556.

• Tsang, Y. P., Choy, K. L., Wu, C. H., Ho, G. T. S., Lam, H. Y., & Tang, V. (2018). An intelligent model for assuring food quality in managing a multi-temperature food distribution centre. Food control, 90, 81-97.

Selected Conference Papers

• Tsang, Y. P., Mo, D. Y., Chung, K. T. & Lee, C. K. M. (2023). Solving Capacitated and Time-constrained Vehicle Routing Problems by Deep Reinforcement Learning-based Method. IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) 2023, Singapore, 18-21 Dec, 2023.

• Tsang, Y. P., Li, Y. L., Lee, C. K. M., & Chen, Z. S. (2023). A Comparative Analysis of Fuzzifying the Best Worst Method. 2023 IEEE International Conference on Fuzzy Systems (FUZZ), Incheon, Republic of Korea, 13-17 Aug, 2023.

  Li, Y. L., Tsang, Y. P., Wu, C. H., & Lee, C. K. M. (2023, March). An Analytics Framework to Evaluate Group Decision-Making Capabilities of the Fuzzy Best Worst Method. In 2023 5th International Conference on Decision Science & Management (ICDSM) (pp. 34-37). IEEE.