This session is organized by the Laboratoire d’analyse géoscientifique et numérique par intelligence artificielle (LAGNIA), a consortium consisting of the Geological Survey of Canada (GSC), the Institut national de la recherche scientifique (INRS), Quebec’s Ministère des Ressources naturelles et des Forêts (MRNF), and France’s Bureau de Recherches Géologiques et Minières (BRGM).
Artificial Intelligence (AI) is rapidly transforming mineral exploration by enabling new approaches for the integration, interpretation, and enhancement of geoscientific data. From machine learning and deep learning methods to AI-assisted 3D geophysical inversion, predictive modelling, remote sensing, and multi-source data fusion, AI is paving the way for more efficient, targeted, and sustainable exploration strategies.
This session aims to bring together researchers, industry professionals, and decision-makers to review methodological advances, practical applications, and case studies related to the use of AI in mineral exploration. Topics may include, without being limited to, the following:
- Multi-scale geoscientific data integration and analysis
- Predictive mineral prospectivity mapping
- AI-assisted geophysical inversion
- Geochemical and hyperspectral data processing
- Critical mineral applications
- Data quality, model generalization, and interpretability challenges
This initiative seeks to strengthen international and inter-institutional collaboration, to accelerate digital innovation in mineral discovery and support critical mineral strategies.