Received Sylff fellowship in 2015.
Current Affiliation: University of Hong Kong
Dr. Xiao LI is currently a research assistant professor at The Hong Kong Polytechnic University and will be the incoming assistant professor at The University of Hong Kong (2022/12/19-). Dr. Xiao LI received his Ph.D. degree from PolyU in 2019, B.Eng degree, and M.Eng degree from Chongqing University in 2013 and 2016, respectively. Before joining PolyU as a Research Assistant Professor of Construction Industrialization, he was an RGC Postdoctoral Fellowship awardee at The University of Hong Kong and assistant director at Qianhai Institute for Innovative Research. He was also a visiting scholar at the University of Cambridge and Curtin University. His research interests mainly focus on construction industrialization and construction informatics. He has led 6 research projects with funding exceeding HK$ 5million and has authored 40+ papers in peer-reviewed academic journals with 2200+ citations (17 first & corresponding authored papers, 3 ESI highly cited, 4 Most cited papers in Automation in Construction). He is a fellow of the SYLFF Association, a National Certified Construction Engineer, a member of CIB and the American Society of Civil Engineers, and guest editors of several leading journals in construction engineering and management. He held several international academic awards, e.g., SYLFF Research Grant Award, Research Abroad Award, CIB Sebestyén Future Leaders Award, ASCE Best Paper Award, and CIOB (HK) Outstanding Paper Award. His research mainly contributes to the smart work packaging methodology for collaborative planning and control in construction.
Brief Summary of Support Program Activities:
1. To formulate and realize a decentralized adaptive work package (DAWP) learning model for personalized monitoring of heterogeneous data in construction occupational health and safety (COHS);
2. To develop and validate a blockchain DAWP (BC-DAWP) approach for privacy-preserving monitoring of COHS data in work packages with appropriate performance metrics; and
3. To integrate and disseminate the proposed BC-DAWP approach on mainstream platforms of COHS monitoring through interfaces.