The amount and variety of data created in the process of measuring and modelling Earth's subsystems are drastically increasing with ever-improving computational and data acquisition capabilities. Data-driven AI/ML methods have significantly enhanced traditional approaches to earth sciences research, giving us new insight into a wide range of Earth processes. Following the inclusion of unconventional and citizen-driven data sources to geoscience applications, Artificial Intelligence (AI) / Machine Learning (ML) methods have enabled the analysis of large data volumes in geosciences that would not have been possible otherwise. This session seeks submissions that fit one of the criteria below:

1. Present novel data-driven AI/ML methods being researched that pertain to Earth science problems
2. Demonstrate the applications of AI/ML methods and algorithms, including deep learning, to understand Earth’s subsystems
3. Showcase data-driven AI/ML research methods that can replace or complement traditional methods
4. Make use of crowdsourced citizen data on understanding or modeling earth systems

• IN - Earth and Space Science Informatics