World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
75
Citations
16935
World Ranking
775
National Ranking
135

Overview

Jack Chin Pang Cheng is affiliated with the Hong Kong University of Science and Technology in China and has a research background primarily situated within the fields of Engineering and Computer Science. Their scholarly work extensively engages with topics related to Building and Construction, Civil and Structural Engineering, and various computational approaches within these domains.

The researcher's notable publication record includes contributions to prominent venues such as Automation in Construction, Advanced Engineering Informatics, SSRN Electronic Journal, Kalpa publications in computing, and the Proceedings of the International Symposium on Automation and Robotics in Construction (ISARC). Their work features a blend of theoretical and applied research, with particular emphasis on integration and optimization technologies for the construction industry.

Key research topics explored by Jack Chin Pang Cheng encompass:

  • BIM and Construction Integration
  • 3D Surveying and Cultural Heritage
  • Infrastructure Maintenance and Monitoring
  • Blockchain Technology Applications and Security
  • Building Energy and Comfort Optimization
  • Occupational Health and Safety Research
  • Cloud Data Security Solutions

Frequent collaborators include Xingyu Tao, H.L. Kwok, Peter Kok-Yiu Wong, Moumita Das, and Vincent J.L. Gan. Collaborative efforts with these co-authors have contributed to advancing interdisciplinary studies within construction engineering and intelligent infrastructure systems.

The following recent papers illustrate the scope and focus of their research output:

  • "Data-driven predictive maintenance planning framework for MEP components based on BIM and IoT using machine learning algorithms," 2020, Automation in Construction
  • "Simulation optimisation towards energy efficient green buildings: Current status and future trends," 2020, Journal of Cleaner Production
  • "A bi-directional missing data imputation scheme based on LSTM and transfer learning for building energy data," 2020, Energy and Buildings
  • "Securing interim payments in construction projects through a blockchain-based framework," 2020, Automation in Construction
  • "Digital Twins for Construction Sites: Concepts, LoD Definition, and Applications," 2021, Journal of Management in Engineering

Their recent studies cover themes such as machine learning applications in predictive maintenance, blockchain frameworks for construction finance, energy-efficient building simulations, and digital twin technology for construction sites.

Best Publications

  • Comparative environmental evaluation of aggregate production from recycled waste materials and virgin sources by LCA

    Md. Uzzal Hossain;Chi Sun Poon;Irene M.C. Lo;Jack C.P. Cheng

  • Data-driven predictive maintenance planning framework for MEP components based on BIM and IoT using machine learning algorithms

    Jack C.P. Cheng;Weiwei Chen;Keyu Chen;Qian Wang

  • A BIM-based system for demolition and renovation waste estimation and planning.

    Jack Chin Pang Cheng;Lauren Y.H. Ma

  • A state-of-the-art review on the integration of Building Information Modeling (BIM) and Geographic Information System (GIS)

    Xin Liu;Xiangyu Wang;Xiangyu Wang;Graeme Wright;Jack Chin Pang Cheng

  • Automated detection of sewer pipe defects in closed-circuit television images using deep learning techniques

    Jack Chin Pang Cheng;Mingzhu Wang

  • A framework for dimensional and surface quality assessment of precast concrete elements using BIM and 3D laser scanning

    Minkoo Kim;Minkoo Kim;Jack Chin Pang Cheng;Hoon Sohn;Chih-chen Chang

  • Mapping between BIM and 3D GIS in different levels of detail using schema mediation and instance comparison

    Yichuan Deng;Jack Chin Pang Cheng;Chimay J. Anumba

  • A service oriented framework for construction supply chain integration

    Jack Chin Pang Cheng;Kincho Law;Hans J. Bjornsson;Albert T. Jones

  • Automated dimensional quality assurance of full-scale precast concrete elements using laser scanning and BIM

    Min-Koo Kim;Qian Wang;Qian Wang;Joon-Woo Park;Jack Chin Pang Cheng

  • Improving air quality prediction accuracy at larger temporal resolutions using deep learning and transfer learning techniques

    Jun Ma;Jack C.P. Cheng;Changqing Lin;Yi Tan

  • Trends and Opportunities of BIM-GIS Integration in the Architecture, Engineering and Construction Industry: A Review from a Spatio-Temporal Statistical Perspective

    Yongze Song;Xiangyu Wang;Yi Tan;Peng Wu

  • Comparative LCA on using waste materials in the cement industry: A Hong Kong case study

    Md. Uzzal Hossain;Chi Sun Poon;Irene M.C. Lo;Jack C.P. Cheng

  • A BIM-based automated site layout planning framework for congested construction sites

    Srinath Shiv Kumar;Jack Chin Pang Cheng

  • BIM-based framework for automatic scheduling of facility maintenance work orders

    Weiwei Chen;Keyu Chen;Jack C.P. Cheng;Qian Wang

  • Quantification of construction waste prevented by BIM-based design validation: Case studies in South Korea

    Jongsung Won;Jack Chin Pang Cheng;Ghang Lee

  • A financial decision making framework for construction projects based on 5D Building Information Modeling (BIM)

    Qiqi Lu;Jongsung Won;Jack Chin Pang Cheng

  • Identifying potential opportunities of building information modeling for construction and demolition waste management and minimization

    Jongsung Won;Jack Chin Pang Cheng

  • Estimation of the building energy use intensity in the urban scale by integrating GIS and big data technology

    Jun Ma;Jack Chin Pang Cheng

  • A review of the efforts and roles of the public sector for BIM adoption worldwide

    Jack Chin Pang Cheng;Qiqi Lu

  • A temporal-spatial interpolation and extrapolation method based on geographic Long Short-Term Memory neural network for PM2.5

    Jun Ma;Yuexiong Ding;Jack C.P. Cheng;Feifeng Jiang

  • Analytical review and evaluation of civil information modeling

    Jack Chin Pang Cheng;Qiqi Lu;Yichuan Deng

Frequent Co-Authors

Irene M.C. Lo
Irene M.C. Lo Hong Kong University of Science and Technology
Kincho H. Law
Kincho H. Law Stanford University
Hoon Sohn
Hoon Sohn Korea Advanced Institute of Science and Technology
Xiangyu Wang
Xiangyu Wang Curtin University
Kam Tim Tse
Kam Tim Tse Hong Kong University of Science and Technology
Chimay J. Anumba
Chimay J. Anumba University of Florida
Chi Sun Poon
Chi Sun Poon Hong Kong Polytechnic University
Chih-Chen Chang
Chih-Chen Chang Hong Kong University of Science and Technology
Ram D. Sriram
Ram D. Sriram National Institute of Standards and Technology
Alexis K.H. Lau
Alexis K.H. Lau Hong Kong University of Science and Technology

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