Peyman was a PhD student at the Department of Infrastructure Engineering, University of Melbourne.

His PhD thesis explored the application of Building Information Modelling (BIM) in property valuation. His aimed to develop an integrated property valuation method leveraging BIM potentials in different phases of valuation. It considered the physical, geographical, environmental, socio-economic and legal factors affecting property valuation. 

He received his master’s degree in GIS and bachelor’s degree in Geomatics Engineering, and has contributed to a variety of research and practical projects in the field of geospatial technology, GIS and Remote Sensing.

Peyman has published several articles in high-ranked scientific journals and conferences, and has undertaken work experience at Food and Agriculture Organization (FAO) of the United Nations, as a GIS and Remote Sensing Expert.

PhD Start and End Dates
Peyman submitted his thesis for assessment in May 2025. He is a Research Fellow at the University of Melbourne.

Publications

• October 2025 – AI, machine learning and BIM for enhanced property valuation: Integration of cost and market approaches through a hybrid model
• October 2024 – Data-driven strategies for affordable housing: a hybrid genetic algorithm-machine learning optimization model in the Melbourne metropolitan area
• August 2024 – Automated land valuation models: A comparative study of four machine learning and deep learning methods based on a comprehensive range of influential factors
• June 2024 – Automating property valuation at the macro scale of suburban development: A multi-step method based on spatial imputation techniques, machine learning and deep learning
• May 2024 – Analysing factors affecting land prices in urbanised areas using machine learning: A basis for future 3D property valuations
• January 2024 – Deep learning-based spatiotemporal analysis and clustering of house price fluctuations and appreciation levels in the different suburbs of Metropolitan Melbourne (Paper ID 21)
• December 2022 – BIM and real estate valuation: challenges, potentials and lessons for future directions
• October 2022 – A framework to integrate BIM with artificial intelligence and machine learning-based property valuation methods