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Email

jafary.p@unimelb.edu.au

Credentials


Position
Research Fellow - Digital Infrastructure
Department of Infrastructure Engineering
ORCID

0000-0001-8449-931X

Dr Peyman Jafary

Research Fellow - Digital Infrastructure
Department of Infrastructure Engineering

16 Scholarly works
0 Projects

HIGHLIGHTS

  • 2026

    Book Chapter

    Land Intelligence for Affordable Housing: An Integrated Optimization, Machine Learning and Policy Framework
    DOI: 10.1201/9781003638308-17
  • 2026

    Journal article

    Artificial intelligence (AI) and machine learning in building information modeling (BIM)-based construction cost estimation: a systematic review
    DOI: 10.1080/10095020.2026.2651578
  • 2025

    Journal article

    AI, machine learning and BIM for enhanced property valuation: Integration of cost and market approaches through a hybrid model
    DOI: 10.1016/j.habitatint.2025.103515
  • 2025

    Journal article

    Deep Learning and Geometric Modeling for 3D Reconstruction of Subsurface Utilities from GPR Data
    DOI: 10.3390/s25206414
  • 2025

    Journal article

    A BIM-based Framework for Building Depreciation Estimation through Maintenance Management Integration
    DOI: 10.5194/isprs-archives-XLVIII-G-2025-687-2025
  • 2025

    Journal article

    AI-augmented construction cost estimation: an ensemble Natural Language Processing (NLP) model to align quantity take-offs with cost indexes
    DOI: 10.1080/15623599.2025.2558070
  • 2025

    Thesis / Dissertation

    Artificial Intelligence (AI) and Building Information Modeling (BIM) for Enhanced Property Valuation
Peyman Jafary

RECENT SCHOLARLY WORKS

  • 2024

    Journal article

    Mixed Reality-Based Concrete Crack Detection and Skeleton Extraction Using Deep Learning and Image Processing
    DOI: 10.3390/electronics13224426
  • 2024

    Journal article

    Data-driven Strategies for Affordable Housing: A Hybrid Genetic Algorithm-Machine Learning Optimization Model in the Melbourne Metropolitan Area
    DOI: 10.5194/isprs-annals-X-4-2024-175-2024
  • 2024

    Journal article

    Automated land valuation models: A comparative study of four machine learning and deep learning methods based on a comprehensive range of influential factors
    DOI: 10.1016/j.cities.2024.105115

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