Publications
Academic research and publications on AI-powered procurement intelligence in construction.
Artificial Intelligence in Construction Procurement: A Framework for Decision Intelligence
Jeremy Huynh | Curtin University | Expected 2026
This thesis investigates the application of machine learning and natural language processing techniques to automate and enhance procurement decision-making in commercial construction projects. The research develops a novel framework for integrating AI-driven scope extraction, tender analysis, and organizational knowledge capture.
Key contributions include: (1) A taxonomy of procurement decision types in commercial construction, (2) A comparative analysis of NLP models for construction document understanding, (3) A prototype AI system demonstrating practical application, and (4) Validation through industry case studies across Australian construction firms.
Forthcoming Publications
Journal articles and conference papers are currently in development as part of the PhD research program. Publications will be listed here upon acceptance.
Research Areas
Natural Language Processing
Applying NLP to construction specifications and tender documents
Machine Learning
Predictive models for subcontractor performance and risk assessment
Decision Support Systems
AI-augmented frameworks for procurement decision-making
Knowledge Management
Capturing and retrieving organizational procurement knowledge
Construction Technology
Digital transformation in the construction industry
Automation
Process automation for repetitive procurement tasks