Imperial College London

Dr Long Chen

Faculty of EngineeringDepartment of Civil and Environmental Engineering

Research Associate in the Digital Twin







Skempton BuildingSouth Kensington Campus





Dr Chen is a Research Associate in Digital Twin with Imperial College London’s “Centre for Systems Engineering and Innovation", and a visiting researcher at The Alan Turing Institute. He works for the Centre for Digital Built Britain (CDBB) funded project “Analysing Systems Interdependencies using a Digital Twin”, and the Data-centric engineering programme's Grand Challenge III “Data-driven Engineering Design under Uncertainty” supported by Lloyds Register Foundation.

His research is in digital twin, building information modelling (BIM), virtual reality/augmented reality (VR/AR), artificial intelligence (AI) and computer vision (CV) applied in construction management. Long is also interested in construction scheduling prediction and monitoring, risk analysis, uncertainty analysis and fuzzy mathematics.

Prior to joining Imperial College, Long obtained B.Eng. (Hons) in Hydraulic Engineering at Tsinghua University, 2014, and PhD in Civil Engineering from the University of Hong Kong, 2018.

Long has collaborated closely with industry partners, government departments and academia for his research, and has authored many publications in academic journals and conferences. He is also an active reviewer for international journals, e.g., Journal of Construction Engineering and Management (ASCE), Building and Environment (Elsevier), Applied Soft Computing (Elsevier) etc.




Chen L, Lu Q, Zhao X, A semi-automatic image-based object recognition system for constructing as-is IFC BIM objects based on fuzzy-MAUT, International Journal of Construction Management, ISSN:1562-3599, Pages:1-15

Lu Q, Lee S, Chen L, 2018, Image-driven fuzzy-based system to construct as-is IFC BIM objects, Automation in Construction, Vol:92, ISSN:0926-5805, Pages:68-87

Zhao X, Pan W, Chen L, 2018, Disentangling the relationships between business model innovation for low or zero carbon buildings and its influencing factors using structural equation modelling, Journal of Cleaner Production, Vol:178, ISSN:0959-6526, Pages:154-165


Guo BHW, Zou Y, Chen L, A REVIEW OF THE APPLICATIONS OF COMPUTER VISION TO CONSTRUCTION HEALTH AND SAFETY, 18th International Conference on Construction Applications of Virtual Reality (CONVR)

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