Overview
Dr. Su obtained his M.Arch in Architectural Design from University Colleage London and Ph.D in Computer Engineering at Cardiff University. His research focuses on big data, machine learning, deep learning, BIM and data standardization that can benefit information exchange in our real life.
Research
Thesis
A BIM and Machine Learning Integration Framework for Automated Property Valuation
With Big Data applications in real estate domain growing fast, computer-aided valuation systems such as AI-enhanced automated valuation models (AVMs) have the potential to address current issues such as low transparency, inaccuracy and inefficiency. On the one hand, while the advantages of Machine Learning for property valuation have been recognized by researchers and professionals, the predictive accuracy and model interpretability of current AVMs still need to be improved. On the other hand, the benefits and opportunities of BIM for property valuation have gradually captured the attention, but little effort has been made on standard data interpretation and information exchange in property valuation process.
This thesis presents a novel system that leverages holistic data interpretation, facilitates information exchange between AEC projects and property valuation, and an improved AVM for property valuation. A mixed research method was adopted combining archival literature research, qualitative and quantitative data analysis. A BIM and Machine Learning (ML) integration framework for automated property valuation was proposed which contains an IFC extension for property valuation, an IFC-based information extraction and an automated valuation model based on genetic algorithm optimized machine learning (GA-GBR).
This research contributes to managing information exchange between AEC projects and property valuation and enhancing automated valuation models. It was suggested that the infusion of BIM, ML and other emerging digital technologies might add value to property valuation and the construction industry.
Supervisors
Publications
2024
- Gao, Y., Li, H., Fu, W., Chai, C. and Su, T. 2024. Damage volumetric assessment and digital twin synchronization based on LiDAR point clouds. Automation in Construction 157, article number: 105168. (10.1016/j.autcon.2023.105168)
2023
- Zhu, X., Li, H. and Su, T. 2023. Autonomous complex knowledge mining and graph representation through natural language processing and transfer learning. Automation in Construction 155, article number: 105074. (10.1016/j.autcon.2023.105074)
2022
- Su, T. 2022. A BIM and machine learning integration framework for automated property valuation. PhD Thesis, Cardiff University.
2021
- Su, T., Li, H. and An, Y. 2021. A BIM and machine learning integration framework for automated property valuation. Journal of Building Engineering 44, article number: 102636. (10.1016/j.jobe.2021.102636)
- An, Y., Li, H., Su, T. and Wang, Y. 2021. Determining uncertainties in AI applications in AEC sector and their corresponding mitigation strategies. Automation in Construction 131, article number: 103883. (10.1016/j.autcon.2021.103883)
2020
- Su, T. and Li, H. 2020. Data exchange analysis for property valuation on sustainability perspective. Presented at: 27th International Workshop on Intelligent Computing in Engineering (EG-ICE 2020), Online, 01-04 July 2020.
2019
- Wang, Y., Liang, L., Lin, X., Su, T., Wang, X. and Xiao, H. 2019. Emissions of nitrogen-based fuel combustion in swirl burner. Energy Procedia 158, pp. 1706-1711. (10.1016/j.egypro.2019.01.397)
- Su, T. and Li, H. 2019. BIM-based machine learning engine for smart real estate appraisal. Presented at: 2nd International Conference on Sustainable Smart Manufacturing, Manchester, United Kingdom, 9-11 April, 2019.