Hasti Shwan

Hasti Shwan, a professional engineer registered with EGBC, brings over 13 years of engineering expertise in geospatial applications and mapping services. As a co-founder of Geomount Inc., he specializes in applying deep learning to high-precision storm and drainage systems using multisensory data collections. He is also a certified drone pilot and flight reviewer from Transport Canada.

Under the guidance of Prof. Pejoohan Tavassoti at the Center for Pavement and Transportation Technology (CPATT), Hasti's research leverages his extensive experience from government road projects. He continuously hones his programming skills, particularly in Python, as a member of the Geospatial Intelligence and Mapping (GIM) Lab, focusing on LiDAR, thermal technology, and machine learning.

Currently, Hasti is working as a senior engineer on environmental projects and leads a pioneering project to develop a digital platform that addresses flood risks and bolsters the resilience of transportation infrastructure. This initiative aims to equip infrastructure managers with decision-support tools for enhanced disaster planning and readiness.

• Ph.D. in Civil Engineering, University of Waterloo,  2023 - Ongoing 
• M.Sc. in Water Resources Engineering, University of Sulaimani, 2013 – 2016
• B.Sc. in Civil Engineering, University of Sulaimani, 2006 – 2010

• Abdullah, H. (2016). Water quality assessment for Dokan Lake using Landsat 8 OLI Satellite images (MSc Thesis, University of Sulaimani). https://doi.org/10.13140/RG.2.2.11499.03360 (Published)
• Abdullah, H. (2016). Water quality index models for Dokan Lake using Landsat 8 OLI satellite images. Presentation at 2016 IEEE Young Professionals Conference on Remote Sensing, Oberpfaffenhofen, Germany.(Presented)
• Abdullah, H. (2017). Water quality assessment using remote sensing & GIS. Presentation at the Society for Conservation GIS Annual Conference (SCGIS 2017), Pacific Grove, California, USA.(Presented)
• Abdullah, H., Al-Khafaji, M., & Ibrahim, H. (2017). Water quality assessment models for Dokan Lake using Landsat 8 OLI satellite images. Journal of Zankoy Sulaimani Part A – Pure and Applied Sciences, 19(3–4 (A)), 25–44. https://doi.org/10.17656/jzs.10630 (Published)
• Abdullah, H., Al-Khafaji, M., & Ibrahim, H. (2018). Assessment of water clarity within Dokan Lake using remote sensing techniques. Journal of Engineering, 23(8), 13–28.(Published)
• Shwan, H., & Tavassoti, P. (2024). Integrating UAV-Based LiDAR and Imaging Data for Semi-Automated Detection of Water Ponding in Pavement Networks. Canadian Journal of Civil Engineering, Canadian Society for Civil Engineering (pp. 1–11). Surrey. (Submitted)
• Abdalla, S., Shwan, H., Li, J., Samuel, S., & Singh, A. (2024).
  UAV-Based Spectral Analysis for Predicting Street Lighting Efficiency. Full-length article received in the ScholarOne Manuscripts Administrative Center for IEEE Transactions on Intelligent Vehicles. (Submitted)
• Shwan, H., Tavassoti, P., & Steelman, P. (2025). An Integrated Multisensory Approach for Non-Destructive Assessment Of Surface And Subsurface Pavement Defects. In Canadian Society for Civil Engineering (CSCE) Annual Conference 2026 (pp. 1–10). Springer, Winnipeg. (Submitted)
• Shwan, H., & Tavassoti, P. (2025). Assessing Climate Impacts on Pavement Performance: Scenario-Based Analysis of Rainfall, Runoff, and Infiltration for Urban Resilience. 58th International Conference on Water Management Modeling (ICWMM), Toronto, Canada. (Presented)