Friday 24 April 2026 12:00pm to 1:30pm
Conference Room, Civil Engineering Building, University of Cambridge
About
The DRF Lunchtime Clinic is delighted to welcome Prof. Fan (Frank) Xue, Associate Professor at The University of Hong Kong (HKU), who will join us to talk about "From Static to Dynamic: Temporal-Spectral-Structural Point Clouds for Digital Twin Construction".
About the talk
Three-dimensional point clouds deliver accurate geometry and visual texture for digital twins in the architecture, engineering, and construction industry. However, conventional point clouds remain inherently static, visually limited, and incapable of revealing subsurface conditions. The limitations undermine real-time replication/updating and predictive maintenance for digital twins and construction 5.0. This talk shares how temporal, spectral, and structural point clouds can be collected and processed to overcome the limitations to enhance digital twin construction min three aspects: temporal (4D time-series for dynamic monitoring and versioning), spectral (multi- and hyper-spectral imaging for material characterization and aging), and structural (subsurface by tomography of GPR, muon, and X-ray scans). Example pilot cases include 4D motion semantics-enabled site monitoring (e.g., heavy module hoisting, nighttime safety vests, and motions), material deterioration assessment, and heritage building subsurface modelling. The enhanced digital twin construction is expected to enable innovations toward smart, resilient, and human-centric construction.
About the speaker
Prof. Fan (Frank) Xue is an Associate Professor and Associate Head for Research with the Department of Real Estate and Construction, The University of Hong Kong (HKU). He is currently an Academic Visiting Fellow at the Department of Engineering, University of Cambridge, and a Visiting Fellow at Hughes Hall, University of Cambridge. Trained as a multidisciplinary engineer, he specializes in applying computational intelligence and automation to solve complex challenges in building and urban environments.
His research spans building/city informatics, including Building/City Information Modeling (BIM/CIM) automation, derivative-free optimization, urban sensing technologies (LiDAR, 4D point clouds, IoT), blockchain applications, and applied machine learning. His research is supported by over HK$21 million in competitive grants and has yielded influential algorithms, projects, and datasets.
He has received over 30 international and local academic awards, including gold medals at international innovation exhibitions, top-ranked challenge awards at CVPR Scan-to-BIM competitions, and best paper recognitions in leading journals and conferences. His work received over 9,000 citations, and he is listed as an ESI Top 1% Researcher (WoS) and a World Top 2% Scientist (Scopus).