This session highlights recent interdisciplinary research combining space and ground observations, advanced models, and technologies on pre-earthquake activities. Events like the 2025 Kamchatka earthquake and Myanmar's M7.7 quake have motivated efforts to develop early detection systems to reduce casualties. Observables such as ground deformation (GNSS, SAR) and pre-quake geochemical, electromagnetic, hydrogeological, and thermodynamic changes have been monitored concerning stress in the lithosphere. Over the past decade, emerging technologies such as advanced machine learning (ML) and artificial intelligence (AI) applied to big data, along with state-of-the-art signal processing tools, have sparked a surge in research on earthquake forecasting and nowcasting. These methods enable the detection of physical earthquake precursors but also require complex computing architectures. Submissions should cover observations, modeling, ML/AI approaches, especially "explainable AI' aligning with geophysical knowledge, cross-disciplinary studies on earthquake forecasting and nowcasting; and the reliability of identified precursors.

• GP - Geomagnetism, Paleomagnetism and Electromagnetism
• IN - Informatics
• S - Seismology
• T - Tectonophysics