MITM11

The rapid growth of planetary datasets from orbiters, landers, rovers, and telescopes presents both unprecedented opportunities and challenges for analysis and interpretation. This session explores how artificial intelligence (AI), machine learning (ML), and big data techniques can transform planetary science by enabling automated mapping, predictive modeling, anomaly detection, and mission planning.

We invite contributions on:

AI applications for planetary surface, atmosphere, and interior analysis

Machine learning for mission data processing and instrumentation optimization

Predictive models for habitability, climate, and exoplanet environments

Integration of heterogeneous planetary datasets through cloud or federated systems

Tools for global collaboration, capacity building, and open planetary data initiatives

This session aims to bring together planetary scientists, data scientists, and technologists to discuss state-of-the-art methods, future challenges, and collaborative opportunities, fostering cross-disciplinary innovation in planetary research.