Submit a session proposal or short course

Propose a session

Session proposals are welcome before December 01, 2026. Please submit your proposal online in the login area or send it via e-mail to iamg2027@nogo.comiamgmembersorg
Session proposals should include a title, summary, a target IAMG journal (https://iamg.org/publications/iamg-journals/) for possible follow-up full papers, and at least two names (one Chair and one Co-Chair or more).
Responsabilities for the session chairs and co-chairs will be to:

Attract 6, 9 or 12 oral presentations + open number of poster presentations
Review all abstracts for their session, accept for oral or posters and make recommendations to authors
Organize the order of the presentations in the allocated time slot before June 1st, 2027
Register to IAMG 2027 and convene the session with the co-chair.
Accept to act as guest editor or reviewers for follow up papers from their session in IAMG journals

Proposed sessions

Until now the following sessions are proposed.

Click on the titles marked

to see a descriptions.

AI-driven Geochemical Anomaly and Mineral Prospectivity Modeling
Emmanuel John M. Carranza, Renguang Zuo
Geochemical anomaly and mineral prospectivity modeling as a computer-based approach to delineate target areas for exploration of certain mineral deposits in a mineral system has evolved from being knowledge driven to artificial intelligence (AI)-driven. The applications of AI in mineral exploration are ever increasing nowadays to address the complexity of relationships among datasets and with known deposit occurrences. The session welcomes submissions for presentations of: (1) novel AI algorithms and applications for recognition and integration of geo-anomalies to support mineral exploration, in 2D or 3D; and (2) novel AI algorithms and applications for analysis and synthesis of a variety of geoscience datasets to model geochemical anomalies and mineral prospectivity and associated uncertainty, in 2D or 3D.
Beyond Conventional Mineral Exploration: Integrating AI, Geomathematics, and Uncertainty-Aware Decision-Making
Behnam Sadeghi, Steven Ergong Zhang, Guillaume Pirot, Fabian Kohlmann, Haicheng Wang
The convergence of artificial intelligence, advanced data analytics, and geomathematics is transforming mineral exploration, enabling more intelligent, efficient, and uncertainty-aware decision-making. This session explores innovative approaches that integrate machine learning, probabilistic modelling, geostatistics, fractal and multifractal analysis, and expert geological knowledge to address complex exploration challenges. Contributions are invited on multisource geological, geochemical, geophysical, and remote-sensing data integration, spatial pattern recognition, anomaly detection, mineral prospectivity mapping, predictive modelling, and exploration targeting. Particular emphasis is placed on uncertainty quantification, model interpretability, human–AI collaboration, and adaptive exploration strategies that enhance decision confidence and sustainability. By bringing together researchers and practitioners across geoscience, mathematics, and artificial intelligence, the session aims to stimulate interdisciplinary collaboration, creative AI-driven brainstorming, and forward-looking ideas that bridge computational intelligence with geological reasoning, ultimately advancing more reliable, transparent, and actionable approaches to mineral discovery.