Dr Mohammad Aminpour is a University Lecturer in Geo-Environmental Engineering and a geotechnical scientist specialising in computational geomechanics, offshore geotechnics, and data-driven engineering. His research integrates advanced numerical modelling, artificial intelligence, machine learning, and digital technologies to address complex challenges in geotechnical and geo-environmental engineering.
He is the Lead of the Intelligent Coastal and Offshore Geotechnics and Infrastructure (ICOGI) Research Group, with research focused on intelligent and computational approaches to coastal and offshore infrastructure, foundation systems, and renewable energy developments.
Dr Aminpour is also the Lead Entrepreneur of the Australian Economic Accelerator AEA Ignite project, Cutting Offshore Wind Energy Costs through AI-Enhanced Foundation Design. The project has received AUD $499,860 in AEA Ignite funding to advance AI-enabled approaches for offshore wind foundation assessment and design.
His broader expertise includes soil and rock mechanics, deep foundations, soil improvement and remediation, uncertainty assessment, contaminant transport, hydrogeology, and ecohydrology. His computational research applies methods including the Finite Element Method (FEM), Discrete Element Method (DEM), and Lattice Boltzmann Method (LBM).
Dr Aminpour also develops data-driven engineering solutions, including machine-learning-based prediction and optimisation frameworks and digital twin approaches for geotechnical and geo-environmental infrastructure. A particular focus of his current research is the application of these technologies to offshore wind energy and foundation engineering.
With more than eight years of industry experience, he has contributed to infrastructure projects involving dams, tunnels, oil and gas facilities, wind energy developments, water infrastructure, roads, railways, mines, and power plants.
Research Leadership
Geotechnical & Geo-Environmental Engineering
AI & Data-Driven Engineering
Hydrogeology & Ecohydrology
Industry Experience
Community Engagement
Hydrogeology CIVE1184 (2024 to present)
Geotechnical Engineering 2 CIVE1108 (2021 to present)
Advanced Hydrogeology CIVE1122 (2024)
Ecohydrology OENG1253 (2025)
Offshore Geotechnics
Machine Learning Data-Driven Solutions in Geo-Environmental Engineering
Uncertainty / Reliability Assessment in Geotechnical Engineering
Computational Geomechanics (Finite Element Method, Discrete Element Method, Lattice-Boltzmann Method, Couple Multi-physics Methods)
Fluid Transport in Porous Media

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