Recent advances in data science and computational methods are transforming planetary science, offering new tools to explore, interpret, and model surface and subsurface features across the Solar System. As ongoing and upcoming missions generate massive volumes of diverse, high-resolution data, the need for robust automation, efficient processing, and selective interpretation becomes critical. In this context, advanced image processing and AI/ML-powered techniques are playing a central role in producing state-of-the-art products such as 3D reconstructions of planetary surfaces, automated tools for detecting and classifying surface features, and integrated systems for analyzing geological, geophysical, and compositional datasets. These technologies are also increasingly essential for integrating data from multiple sources, enhancing the interpretability of complex planetary environments, uncovering interrelated processes and, on a more practical level, supporting the autonomy and operational efficiency of in-situ exploration resources.
This session invites contributions that showcase innovative applications of these methods in planetary science. We welcome submissions addressing the latest image processing and AI /ML advances, including but not limited to the following topics: