Understanding earthquake source processes remains a central focus in seismology, with critical implications for tectonic processes, hazard assessment, and risk mitigation. This session aims to bring together diverse contributions that explore the physical mechanisms driving earthquakes across different tectonic settings—including both interplate and intraplate events, as well as induced seismicity—at all temporal scales. We welcome submissions spanning detailed case studies of specific seismic sequences to global-scale analyses, utilizing observational techniques, numerical modeling, and laboratory experiments. Studies that integrate multiple methodologies or harness emerging technologies and novel datasets are especially encouraged. Relevant topics include, but are not limited to, physical modeling and observational studies of earthquake source characterization, nucleation process, rupture dynamics, and stress evolution, and the use of machine learning and artificial intelligence for phase detection, catalog enhancement, clustering, and forecasting. By fostering interdisciplinary dialogue, this session seeks to advance our fundamental understanding of earthquake processes and support the development of more effective strategies for seismic hazard assessment and mitigation.

• 10:30 am – 10:45 am | Integrating Machine Learning and Statistical Seismology to Characterise and Forecast Induced Seismicity in the Montney Play, Western Canada – Ramin M.H. Dokht
• 10:45 am – 11:00 am | Earthquake Declustering of Canadian Seismicity using Supervised Machine Learning – Gabriela Perez
• 11:00 am – 11:15 am | Rupture Directivity of Hydraulic Fracturing-Induced Microseismicity: A Case Study from the Kaybob-Duvernay Region – Masooma Hasnain
• 11:15 am – 11:30 am | Time-lapse in-situ Vp/Vs analysis of hydraulic-fracturing–induced seismicity in China and Canada: Similarities and differences – Jian Xu
• 11:30 am – 11:45 am | Describing the uncertainty of earthquake focal mechanisms – Alexandre Plourde
• 11:45 am – 12:00 pm | Double-Ratio Focal Mechanism Inversion – Miao Zhang