Subtheme 20.1: AI for Engineering Geology: Recent Advances and Emerging Frontiers
Session Convener: Dr. Ashok Dahal, Assistant Professor of AI for Early Warning Systems, University of Twente, Netherlands
Email: [email protected]
Session Coordinators:
Session Description
Recent advancements in artificial intelligence (AI) have significantly enhanced both the accuracy and efficiency of modeling regional-scale processes in engineering geology, such as landslides. Despite this progress, several scientific questions remain open—particularly regarding the reliability, quality, transferability, applicability, and explainability of AI models. These aspects are crucial for the integration of AI into engineering practice and informed decision-making. This session will explore recent developments in predictive and explainable AI models, the associated challenges, and the future directions necessary to support the engineering geology community.
Aim of the Session
This session aims to promote an open and constructive discussion on the role of AI in advancing the field of engineering geology, with a particular emphasis on regional-scale applications—where traditional process-based modeling is often limited by data scarcity and high computational costs. We seek to critically examine whether current AI research is genuinely driving scientific innovation and practical application in engineering geology. Additionally, the session will provide a platform to identify existing gaps and outline pathways for improving AI-driven approaches to better serve the scientific and practical needs of the community.