Dr Long Chen

BEng PhD AMASCE MCIOB

Pronouns: He/him
  • Lecturer in Surveying

Research groups and centres

Publications
ORCiD Google Scholar
Long Chen

Research and expertise

My research expertise lies within digital construction and operation monitoring, which is established within Building Information Modelling (BIM), digital twin, computer vision and data-driven approaches. I am particularly interested and have rich experience in:

  • Common data environments from BIM to digital twin
  • Digital twin for construction sites and O&M management
  • Construction schedule monitoring and prediction (for complex projects)
  • Digital sustainability and resilience

Recently completed research project(s)

  • Centre for Digital Built Britain (CDBB) funded general project: Analysing Systems Interdependencies Using a Digital Twin

Recent publications

  • Chen, L., Lu, Q.*, and Zhao, X. (2020) Rethinking the Construction Schedule Risk of Infrastructure Projects Based on Dialectical Systems and Network Theory, Journal of Management in Engineering, 36(5), 04020066.
  • Lu, Q., Chen, L.*, Li, S., and Pitt, M. (2020) Semi-automatic geometric digital twinning for existing buildings based on images and CAD drawings, Automation in Construction, 115, 103183.
  • Chen, L., Lu, Q.*, and Zhao, X. (2019) A semi-automatic image-based object recognition system for constructing as-is IFC BIM objects based on fuzzy-MAUT, International Journal of Construction Management, pp. 1-15.
  • Chen, L.*, and Pan, W. (2018) Fuzzy set theory and extensions for multi-criteria decision-making in construction management, Fuzzy hybrid computing in construction engineering and management: Theory and applications, edited by AR Fayek, 179-228.
  • Lu, Q., Lee, S.*, and Chen, L. (2018) Image-driven fuzzy-based system to construct as-is IFC BIM objects, Automation in Construction, 92, pp. 68-87.
  • Lu, Q., Chen, L., Lee, S.*, and Zhao, X. (2018) Activity theory-based analysis of BIM implementation in building O&M and first response, Automation in Construction, 85, pp. 317-332.
All publications

Profile

I am currently a Lecturer/Assistant Professor at the School of Architecture, Building and Civil Engineering at Loughborough University.

Before joining Loughborough, I worked as a Research Associate at Imperial College London’s Centre for Systems Engineering and Innovation, and as a researcher of the Data Centric Engineering Programme at The Alan Turing Institute. I worked 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 the Lloyds Register Foundation.

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

I have collaborated closely with industry partners, government departments and academia for my research, and have authored many publications in academic journals, book chapters and conferences. I am also an active reviewer for international journals, e.g. Journal of Construction Engineering and Management (ASCE), Journal of Management in Engineering (ASCE), Automation in Construction, Building and Environment, Applied Soft Computing etc.

Professional affiliations

  • Member, The Charted Institue of Building (CIOB)
  • Associate Member, American Society of Civil Engineers (ASCE)
  • Member, International Council on Systems Engineering (INCOSE)

Awards

  • 2016 - Best Paper Award, The CIB World Building Congress (WBC16) Intelligent Built Environment or Life, Tampere, Finland
  • 2015 - HKSAR Government Scholarship-Talent Development Scholarship (TDS)
  • 2014 - Hong Kong PhD Fellowship (HKPF)
  • 2014 - National Outstanding Graduate in Hydraulic Engineering Award

External activities

  • Editor (Chinese Language), BIM Dictionary, BIMe Initiative (https://bimdictionary.com/)

  • Visiting Researcher, The Alan Turing Institute