# Event Details - **Event Name**: SDM: Machine Learning Advances for Rare Events in Earth | Non-Fellow Ticket - **Event Start and End Date**: Fri, 09 Jan, 2026 at 10:00 am – Fri, 09 Jan, 2026 at 03:35 pm - **Event Description**: This is part of our Specialist Discussion Meeting Programme. Hybrid Event. This ticket is for Non-Fellows only.About this EventSpecialist Discussion Meeting:Machine Learning advances for Rare Events in Solid Earth ScienceOur Specialist Discussion centres upon the transformative potential of recent machine learning advances during the most critical moments when earthquakes, tsunamis, and volcanic eruptions threaten livelihoods, the natural environment, and human lives. These catastrophic events demand immediate, high-resolution data products that traditionally required days to months for generation. Advanced ML algorithms combined with cloud computing infrastructure present extraordinary opportunities to revolutionise scientific emergency response capabilities. The above may have transformative power on scientific response in the near future touching upon a range of topics: from the rapid deployment of optimised monitoring networks, the generation of descriptive datasets that clarify the evolving earthquake and volcanic activity in extraordinary detail, and the development of hybrid forecast models that leverage ML to predict aftershock sequences, volcanic eruption patterns, and tsunami propagation with unprecedented accuracy among others.Distinguished invited speakers from leading US and EU universities and research institutes will present cutting-edge developments in ML-driven solid earth science. These presentations, combined with showcase studies from early career scientists, will illuminate transformative examples demonstrating real-world impact. Our comprehensive round table discussion will engage senior researchers, emerging scientists from solid earth and data science communities, alongside decision-makers and disaster mitigation specialists to address both scientific advancement opportunities and the challenges that lie ahead for ML-based disaster response systems.Programme:10:00-10:30 CoffeeMorning Session Science Talks (10:30-13:00) - every slot involves a 20 min talk, plus questions1. Earthquakes10:30-10:55 Prof. Beroza, G. (Stanford University), Towards Reliable Machine Learning for Earthquake Monitoring10:55-11:20 Dr. Scotto Di Uccio, F., From background seismicity to seismic crises: What can we learn from Machine Learning-Enhanced Catalogs? (University of Napoli)2. Volcanoes11:20-11:45 Dr. Prejean, S., Key challenges in Eruption Forecasting, (Volcano Assistance Disaster Program, US Geological Survey)11:45-12:10 Dr. Zali, Z., Machine Learning for Transients in Solid Earth: Across Active Faults and Volcanoes, (GFZ Helmholtz-Zentrum fur Geoforschung)3. Tsunamis12:10-12:35 Lorito, S., Machine Learning for tsunami forecasting. An overview. (Instituto Nationale di Geofisica e Vulcanologia-Roma)12:35-13:00 Ramalingam, N., Making probabilistic tsunami hazard assessment "fast" with ML, (Norwegian Geotechnical Institute)13:00-14:00 Lunch BreakAfternoon Session (14:00-15:30)Round Table around the topic, the value of reliable scientific information for emergency response in natural disasters14:00-14:15 Problem Statement by Prof. Synolakis14:15-15:15 Round table with scientists, relevant stakeholders, emergency responders15:15-15:30 Closing remarks15:30-16:00 Coffee break - **Event URL**: https://allevents.in/london/sdm-machine-learning-advances-for-rare-events-in-earth-|-non-fellow-ticket/100001498625873329 - **Event Categories**: meetups, it - **Interested Audience**: - total_interested_count: 0 ## Ticket Details - **Ticket URL**: https://consumer.pxf.io/c/1339408/3151484/39691?partnerpropertyid=1191892&MediaPartnerPropertyId=1191892&svlink=14105511&level=1&u=https%3A%2F%2Fwww.eventbrite.com%2Fe%2Fsdm-machine-learning-advances-for-rare-events-in-earth-non-fellow-ticket-tickets-1498625873329 - **Ticket Price Range**: min: 6.13, max: 16.96, currency: GBP ## Event venue details - **city**: London - **state**: EN - **country**: United Kingdom - **location**: The Royal Astronomical Society - **lat**: 51.5085836 - **long**: -0.13938120000000254 - **full address**: The Royal Astronomical Society, Piccadilly, London, United Kingdom ## Event Organizer details - **affiliate_id**: 10 - **organizer**: Royal Astronomical Society (https://allevents.in/org/royal-astronomical-society/22518426) ## Event gallery - **Alt text**: banner - **Image URL**: https://cdn-az.allevents.in/events7/banners/e14d6817edaf7b922aa5b79465637c66ee92da1029d6eb35f78c9985882d9c22-rimg-w940-h470-dcffffff-gmir.jpg?v=1761945383 - **Alt text**: thumbnail - **Image URL**: https://cdn-az.allevents.in/events7/banners/9fe6c069cbfc8b956d052e35881fc6e9062dd261f522a9c82d8037c135ae7386-rimg-w400-h400-dcffffff-gmir.jpg?v=1761945383 ## FAQs - **Q**: When is the event happening? - **A:** Fri, 09 Jan, 2026 at 10:00 am - **Q**: Where is the event happening? - **A:** The Royal Astronomical Society, Piccadilly, London, United Kingdom - **Q**: What is the ticket price? - **A:** starting from 6.13 up to 16.96 GBP - **Q**: Who is organizing the event? - **A:** Royal Astronomical Society - **Q**: What type of event is this? - **A:** meetups, it - **Q**: Where can I find ticket details about SDM: Machine Learning Advances for Rare Events in Earth | Non-Fellow Ticket ? - **A:** You can find ticket details about this event on AllEvents. ## Structured Data (JSON-LD) ```json [ { "@context": "https://schema.org", "@type": "Event", "name": "SDM: Machine Learning Advances for Rare Events in Earth | Non-Fellow Ticket", "image": "https://cdn-az.allevents.in/events7/banners/e14d6817edaf7b922aa5b79465637c66ee92da1029d6eb35f78c9985882d9c22-rimg-w940-h470-dcffffff-gmir.jpg?v=1761945383", "startDate": "2026-01-09", "endDate": "2026-01-09", "url": "https://allevents.in/london/sdm-machine-learning-advances-for-rare-events-in-earth-|-non-fellow-ticket/100001498625873329", "location": { "@type": "Place", "name": "The Royal Astronomical Society", "address": { "@type": "PostalAddress", "streetAddress": "Piccadilly", "postalCode": "W1J 0BQ", "addressLocality": "London", "addressRegion": "EN", "addressCountry": "GB" }, "geo": { "@type": "GeoCoordinates", "latitude": "51.5085836", "longitude": "-0.13938120000000254" } }, "eventAttendanceMode": "https://schema.org/OfflineEventAttendanceMode", "description": "This is part of our Specialist Discussion Meeting Programme. 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