Artificial intelligence (AI) and data science are transforming our capabilities to model and manage complex processes in subsurface hydrology and energy. This session invites innovative applications of AI, including machine learning, deep learning, and large language models, to groundwater flow, contaminant transport, geothermal energy, underground energy storage, and hydrocarbon recovery. This session will focus on solving problems related to not having enough data, having different types of data, uncertainty in AI models, simplified models, and variations at different scales, as well as combining AI with physics-based models, lab tests, and real-world data. We encourage contributions that discuss interpretability, robustness, and the deployment of AI in decision-making for sustainable energy and subsurface water resources. This session provides a chance for hydrologists, hydrogeologists, geoscientists, energy researchers, and data scientists to work together, share knowledge, and push the boundaries of AI in studying underground resources.

• MR - Mineral and Rock Physics