Vision and Mission
Data-driven and Computational Geotechnics (D&CG) research team mission is to develop innovative solutions to tackle real-world challenges in infrastructures, energy, building, and transport sectors, in relation to geomechanics and geotechnical engineering. Our vision is to advance and enable data-driven/AI and computational methods for forecast, prediction, simulation, and uncertainty assessments focusing on geotechnical design, geohazards, geo-failures, and extreme events in geo-structural systems.
Join Us
Students, Researchers, industry and government partners are encouraged to contact us for research positions, collaboration and partnership opportunities.
Focus Areas of Research:
- Prediction and Early Warning of Pier/bridge Scour
- Early Detection of Internal Erosion in Earth Dams
- Geo-failures prediction and prevention: Slopes, Tailing dams, Rock Mass
- Constitutive Modeling of Geomaterials
- Dynamic Soil-Structure Interaction Analysis Under Extreme Events: Impacts, Seismicity, Explosion
- Intelligent Geotechnical Site Characterization and Ground Modeling
- Uncertainty Quantification, Probabilistic and Reliability Analysis in Geotechnics
- Pile Design
- Renewable Energy and Sustainability
Methodology Research:
- Artificial Intelligence and Machine Learning: Deep Learning (DL), Generative AI (LLM), Explainable AI (XAI)
- Physics-Inspired and Physics-Informed Machine Learning (PINN)
- Numerical Simulations: Finite Elements (FEM), Discrete Elements (DEM), Computational Fluid Dynamics (CFD)
- Computational Probabilistic Methods: Bayesian Inference, Stochastic Surrogate Modeling, Random Fields
Team lead
Research Fellows
Graduate Researchers
Past Members
Dr Oscar Correa
Current Position: Director of AI Research at EXIT83, US
Highlights
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AI early warning for bridge scour
Scour is number one cause of bridge failure in the world. Existing models struggle to predict scour depth with reliable accuracy. We have developed ScourCast, an AI-based platform for real-time prediction of scour in site-specific and regional bridges.
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Internal Erosion in Earth Dams
Internal erosion is the major cause of earth dam failure in Australia and worldwide. We are developing advanced a new early detection and warning framework for internal erosion in earth dams using anomaly detection AI algorithms, advanced sensing methods and physical modeling experimentation.
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Crash Simulations for Road Barriers
Nonlinear soil-pile interaction under dynamic impact is an essential mechanism in piled flexible barriers in road safety. We have developed advanced soil constitutive models for more accurate and cost-effective barrier design. In addition, we have introduced new surrogate modeling approach for efficient reliability based optimisation of road barriers.
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Smart Site Investigation
We are developing new site characterisation methods using advanced AI and probabilistic modeling based on CPT and FFP methods.
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Offshore Geohazards
Grants
Please refer to Dr Negin Yousefpour for latest research grants.
Publications
No results were found
We offer a range of consultancy services in advanced AI-based geotechnical design, geo-structural design, numerical modelling, geotechnical site characterization and geotechnical interpretation. For more information please contact Negin Yousefpour.
Active Projects
PhD students welcome to following opportunities
- Scour early warning, physical modeling, numerical simulation and predictive ML modeling
- Internal erosion early detection: physical modeling, numerical simulation and AI early warning
- AI-driven and probabilistic site characterisation and interpretation
- Offshore geotechnics
- Offshore geohazards assessment
- Soil-structure interaction simulations for impact: road and bridge approach barriers
Students are encouraged to send their expression of interest by emailing Negin Yousefpour. Please include a cover letter, cv, transcripts and sample publications