Mr. Milad Baghalzadeh Shishehgarkhaneh
Mr. Milad Baghalzadeh Shishehgarkhaneh
Milad completed his PhD in Civil Engineering at Monash University, Melbourne, Australia. He is also Monash’s Industry Affair Representative in 2024.
His research is primarily focused on leveraging advanced Artificial Intelligence (AI) methodologies, notably Transformer architectures, to address challenges in construction supply chain risk management. Additionally, Milad is exploring the integration of AI with Blockchain technology to enhance resilience in construction projects.
With over 40 published works, including journal articles and book chapters, Milad has made significant contributions to the field. His diverse research interests encompass construction supply chain management (CSCM), machine learning, natural language processing (NLP), blockchain technology, and Building Information Modelling (BIM). Through his academic endeavours, Milad aims to drive innovation in construction management practices, ensuring projects are executed efficiently and resiliently amidst evolving industry challenges.
Recognized as a ‘Rising Star’ in Australian Research by The Australian in 2024.
Qualifications
- Masters of Science, Construction Management, Azad University of Tabriz, Iran, 2021
- Bachelor of Civil Engineering, Azad University of Tabriz, Iran, 2018
- PhD in Civil Engineering, Monash University , 2026
Research Projects
Current projects
Resilient Supply Chain Risk Management in Australian Infrastructure Projects: A Blockchain-enabled Reinforcement Learning approach
The project focuses on the development of a Blockchain-enabled Reinforcement Learning approach to improve resilient supply chain risk management in Australian infrastructure projects. It aims to enhance the decision-making process in construction supply chains by integrating advanced technologies such as blockchain and AI for better resource management and risk mitigation.
A Theoretical Framework for Digital Shadows in Smart Infrastructure
This project aims to develop a comprehensive theoretical framework for the application of digital shadows in smart infrastructure systems. It involves a systematic literature review across Scopus, Web of Science, and IEEE Xplore, using PRISMA guidelines to identify and synthesise research works published between 2015 and 2025. Key areas of focus include asset management, data integration, IoT, and user interface design within buildings and bridges. The study integrates thematic analysis and bibliometric mapping using VOSviewer to identify research gaps and common patterns, supporting the conceptualisation of digital shadow models for infrastructure monitoring and performance optimisation.
Past projects
AI and BIM Application for Construction Resource Optimization
This project investigates the application of Artificial Intelligence (AI) and Building Information Modeling (BIM) to optimize resource allocation in construction projects. The goal is to integrate these technologies to improve construction processes by minimizing waste, reducing costs, and enhancing overall project efficiency.
How to Use AI to Detect, Predict, and Manage Modern Slavery Risks in Your Supply Chains?
This project investigates the application of advanced artificial intelligence techniques—particularly natural language processing (NLP) and transformer-based models such as BERT—for detecting, predicting, and mitigating modern slavery risks in global supply chains. Funded by the University of South Australia Business School, the study explores how AI can automate the analysis of corporate disclosures, news media, and third-party reports to identify patterns of labour exploitation and support regulatory compliance, ethical sourcing, and ESG risk management.
Optimization of Infrastructure Projects Resources Using Metaheuristic Algorithms and BIM
This project involved the use of metaheuristic algorithms combined with Building Information Modeling (BIM) to optimize resource allocation in infrastructure projects. The focus was on improving project outcomes by integrating advanced optimization techniques to enhance resource efficiency and reduce overall project costs.
You can access my publications through this link.
Monash Graduate Scholarships (MGS)
Teaching Commitments
- OPM5000 - Organising the Project Function
- CIV2206 - Structural mechanics