Dr Mingzhu Wang

BEng PhD

  • Senior Lecturer

Research and expertise

I joined Loughborough University in 2020 as a Lecturer in Construction Management after working at Imperial College. My research interests broadly include the application of advanced computing techniques and information technologies in construction management, such as computer vision, machine learning, artificial intelligence, building information modelling (BIM) and Internet of Things (IoT).

I am particularly interested and have experience in the following areas:

  • Civil infrastructure monitoring and condition assessment
  • Construction progress and safety monitoring
  • Underground utility management / Facility management
  • BIM and GIS integration
  • Digital twin

I have several publications in high-impact journals, conference proceedings, and have presented my works at international conferences and workshops. I have collaborated with academia and industry partners from different countries and regions.

Enquiries on pursuing a PhD in the areas of my research interest are highly welcome. 

Recently completed research projects

  • Scan-vs-BIM for construction progress monitoring - a collaboration with Contilio and funded by Innovate UK

Recent publications

  • Luo, H., Wang, M.*, Wong, P.K.Y. and Cheng, J.C.P. (2020) Full body pose estimation of construction equipment using computer vision and deep learning techniques, Automation in Construction, 110, 103016. doi:10.1016/j.autcon.2019.103016.
  • Wang, M. and Cheng, J.C.P.* (2019) A unified convolutional neural network integrated with conditional random field for pipe defect segmentation, Computer-Aided Civil and Infrastructure Engineering. mice.12481. doi:10.1111/mice.12481.
  • Wang, M., Deng, Y.*, Won, J. and Cheng, J.C.P. (2019) An integrated underground utility management and decision support based on BIM and GIS, Automation in Construction, 107, 102931. doi:10.1016/j.autcon.2019.102931.
  • Cheng, J.C.P. and Wang, M.* (2018) Automated detection of sewer pipe defects in closed-circuit television images using deep learning techniques, Automation in Construction, 95, 155–171. doi:10.1016/j.autcon.2018.08.006.
  • Kumar, S.S.*, Wang, M., Abraham, D.M., Jahanshahi, M.R., Iseley, T. and Cheng, J.C.P. (2020) Deep learning-based automated detection of sewer defects in CCTV videos, Journal of Computing in Civil Engineering, 34. doi:10.1061/(ASCE)CP.1943-5487.0000866.


I contribute to learning and teaching activities across the School's programmes, including:


  • CVB112 – Construction Finance and Risk


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

Prior to joining Loughborough University in 2020, I was a Research Associate at the Centre for Systems Engineering and Innovation (CSEI) at Imperial College London. I worked on a project titled “Scan-vs-BIM for construction progress monitoring”, which is a collaboration with Contilio and funded by Innovate UK.

Before working at Imperial College London, I received my BEng degree in Construction Management from Guangzhou University in 2015, after which I obtained my PhD in Civil Engineering from the Hong Kong University of Science and Technology (HKUST) in 2019. During the four years of my PhD studies, I have been to the RAAMAC lab at the University of Illinois Urbana-Champaign as a visiting scholar, working on computer vision for construction site monitoring.

Professional affiliations

  • Visiting researcher at The Alan Turing Institute, Imeprial College London


  • The ADF 2019 - The Rising Stars Women in Engineering Workshop Nomination, HKUST, 2019
  • First Prize in BIM-CIM Innovation Competition, Shenzhen, China, 2018
  • Best Paper Award, the 18th  International Conference on Construction Application of Virtual Reality (CONVR 2018), Auckland, New Zealand, 2018
  • Category F - Research Award at the HKIPM Project Management Awards, Hong Kong, China, 2016
  • Outstanding Students Award at the Autodesk Hong Kong BIM Awards, Hong Kong, China, 2016