Short Bio
I am a PhD Candidate in Construction Engineering and Management at the Department of Civil and Environmental Engineering, Monash University. I am based in the ICON Lab, led by Dr Yihai Fang, and my PhD is supervised by Dr Yihai Fang and Dr Songbo Hu.
My research focuses on construction automation, construction informatics, knowledge graphs, multi-modal data fusion, computer vision, and automated crane lift monitoring. I am particularly interested in construction productivity, efficiency, and performance analytics.
My work aims to improve the efficiency, safety, and practical deployment of data-driven and knowledge-based smart construction systems by transforming construction-site sensor, image, and operational data into interpretable monitoring and productivity insights.
Education
- 2022–2027 (Expected) PhD in Construction Engineering and Management, Monash University, Australia
- 2019–2022 Master of Advanced Engineering (Civil Engineering – Infrastructure Systems), Monash University, Australia
- 2014–2018 Bachelor of Engineering in Engineering Mechanics, Nanjing University of Science and Technology, China
Links
Email: Junlin.Wang@monash.edu
Google Scholar: Junlin Wang
LinkedIn: junlin-wang-99a451190
ORCID: 0009-0000-8355-5746
GitHub: WJunlin616
Selected Publications
- Wang, J., Hu, S., Fang, Y., & Guo, H. (2026). Knowledge-augmented multi-modal data fusion and reasoning for automated crane lift monitoring. Automation in Construction, 183, 106822. doi:10.1016/j.autcon.2026.106822
- Hu, S., Wang, J., & Fang, Y. (2024). Semantic Web-assisted progress monitoring of crane operations in construction projects. Proceedings of the Institution of Civil Engineers – Smart Infrastructure and Construction, 1–10.
- Fang, Z., Hu, S., Wang, J., Fang, Y., & Lu, Q. (2025). Ontological models for construction scheduling and resource planning. In W. Lu & C. J. Anumba (Eds.), Routledge Handbook of Smart Built Environment (Chapter 9). Routledge.
- Hu, S., Wang, J., & Fang, Y. (2023). Semantic Web-assisted progress monitoring of crane operations in construction projects. In Proceedings of the 30th EG-ICE International Conference on Intelligent Computing in Engineering (pp. 154–163). EG-ICE.
Research Keywords
Construction automation, smart construction, construction informatics, knowledge graphs, ontologies, multi-modal data fusion, computer vision, construction robotics, construction productivity and performance analytics.
Technical Skills
Python, SQL, MATLAB, Neo4j/Cypher, ontology engineering, graph-based reasoning, data visualisation, computer vision, machine learning, tree-based models, deep learning, CNNs, RNNs, attention/Transformers, and large language models (LLMs).
Quantitative Modelling Skills
Complex data forecasting, complex model research, feature engineering, time-series/cross-sectional modelling, model validation, and performance evaluation.
Awards
- 11th Place in the WorldQuant International Quant Championship Global Final Stage 3; 2nd Place in Regional Stage 2
- WorldQuant BRAIN Gold Level
- Kaggle Jane Street Silver Medal
- Kaggle Yale/UNC-CH Bronze Medal
- Top 5% in the Kaggle DRW Crypto Market Prediction Competition
Teaching and Research Activities
UNSW Smart Construction teaching assistant; research assistant, Monash research assistant, WSU research assistant