This webinar explores how generative AI (GenAI) is transforming geotechnical engineering by enabling automated numerical modelling, using tools that include Python scripting and PLAXIS. It demonstrates how engineers can streamline modelling workflows, reduce manual effort, and efficiently assess multiple design scenarios—making advanced analysis more practical for everyday engineering applications.

The session also highlights the role of automation in generating synthetic datasets through large-scale parametric studies. These datasets support data-driven decision-making, optimisation, and future machine learning applications. Real-world case studies will illustrate how these approaches improve design efficiency, reliability, and sustainability in geotechnical practice.

What you will learn:

How to implement automated numerical modelling workflows using Python and geotechnical software (e.g. PLAXIS). How GenAI can assist engineers in developing, debugging, and scaling automation with limited coding experience. How to generate and utilise synthetic datasets for parametric studies and data-driven design. How automation supports better decision-making, optimisation, and sustainable geotechnical design.