Academic Staff
- ZN732
- +852 2766 5824
- hannan.qureshi@polyu.edu.hk
Biography
Dr. Qureshi earned his Ph.D. degree from Universiti Teknologi PETRONAS (UTP), Malaysia, in Civil Engineering, in 2023. He also received his M.S. in Construction Management from the National University of Sciences & Technology (NUST), Pakistan, in 2014. Dr. Qureshi joined PolyU in September 2023 as a Postdoctoral Researcher. Overall, he has versatile experience, including six years of construction industry experience and more than four years of teaching experience.
Dr. Qureshi’s doctoral research focused on real-time monitoring of construction processes. His Ph.D. work resulted in one patent and two copyrights, demonstrating his ability to translate advanced research into practical, industry-ready solutions. During his postdoctoral research, he advanced non-destructive evaluation (NDE) of infrastructure by pioneering the Optimum Thermal Gradient Thresholds (OTGT) system for the detection of anomalies in concrete structures using infrared thermography.
Dr. Qureshi strongly believes in applying AI to develop smart and intelligent solutions. His primary expertise is in technology-based infrastructure and asset management. He has broad research capabilities and demonstrates strong competency in programming languages, BIM, photogrammetry, and infrared thermography using drones and standalone cameras. Dr. Qureshi has authored or co-authored various peer-reviewed publications, published by leading publishers such as Elsevier, Springer, and CRC Press, and his work has been cited by researchers. His major research areas include smart construction process monitoring and NDT for infrastructure/building performance monitoring. However, he remains open to innovative ideas and new pathways that contribute to the advancement and betterment of the professional industry.
Research Interests
Construction 4.0: Data-Driven Process and Site Management
Smart Condition Assessment and Structural Health Monitoring
Building Information Modeling (BIM) & Digital Twins
AI-Driven Solutions (Research & Construction Management Domain)