Artificial intelligence and machine learning are transforming how we observe, model, and predict the behaviour of the cryosphere. By combining data-driven approaches with physical understanding, AI enables new ways to accelerate forward and inverse models, to fuse diverse remote sensing and in situ observations, and to quantify uncertainty in projections of ice dynamics and sea-level rise. This symposium invites contributions that explore the development, evaluation and application of AI methods across glaciology, from physics-informed machine learning that embeds conservation laws into neural surrogates, to deep learning for automated interpretation of optical, radar and lidar imagery; from Bayesian and ML-based inversions for subglacial mapping to data-driven downscaling of climate and ocean forcings at ice margins. We welcome work on emulators and hybrid models that accelerate probabilistic ensemble projections, AI-assisted parameter tuning and model coupling, and studies that integrate sparse observations with prior physical knowledge to improve resolution and uncertainty characterization. Both methodological advances and demonstrative applications, including operational monitoring, process-level insights, and cross-disciplinary integration, are encouraged. Contributions addressing model evaluation, interpretability, data and code sharing, and the societal implications of AI-enabled cryospheric sciences are particularly welcome.

We seek papers and presentations on any timely topic related to Artificial Intelligence in Glaciology. Key focus areas include (but are not limited to):

1. Physics-Informed Machine Learning for Ice Processes
   • Integrating physical laws and conservation principles into ML models
   • Emulation and acceleration of forward and inverse models using neural networks
   • ML-based emulators for probabilistic sea level rise projections
   • Data-driven discoveries broadly defined
2. Remote Sensing and Image Analysis for Glacier and ice sheet Monitoring
   • ML for interpreting optical, radar, and lidar imagery
   • Automated rift, supraglacial lakes, calving front, grounding lines and iceberg detection
   • Time-series analysis for monitoring changes in snow and ice cover
3. AI for Subglacial and Bedrock Mapping
   • Bayesian and ML-based inversion of gravity, radar, and seismic data
   • Enhancing resolution and uncertainty characterization of subglacial topography and internal layer annotation
   • Integration of sparse observations with prior knowledge using ML
4. ML-aided climate and ocean forcing of ice sheets
   
   • Data-driven downscaling of climate and ocean reanalyses to ice sheet margins
   • Learning spatiotemporal patterns of melting and ice-ocean interaction
   • AI for coupling ice sheet models with climate models or ocean models
5. Other use of AI in glaciology
   
   • AI-based visualization for science communication
   • Custom LLMs to support glaciologists.

The list of abstracts is available here.

The Council of the IGS has decided to publish a thematic issue of the Annals of Glaciology on topics consistent with the Symposium theme (Artificial Intelligence in Glaciology). Participants and nonparticipants alike are encouraged to submit manuscripts for this Annals collection. The Associate Chief Editor for this Annals collection will be Mathieu Morlighem. The Call for Papers is available here.

We are happy to offer some small conference grants to partially support early career scientist travel and attendance. These funds will be administered together with the regular call for grants managed by the IGS-EGG. More information is available here. Please note the application deadline of 31 January 2026. Notifications of funding will be sent to all applicants prior to the deadline for early registration.

Please note that the fees include Icebreaker, mid-week excursion, all lunches and coffee break refreshments, and conference dinner.

An early-bird discount of $50 will be applied before 9 April 2026, and a late fee surcharge of $150 will be added after 2 June 2026.

On Thursday afternoon (June 25th), there will be three organized excursions. All excursions will plan to return to downtown Hanover in the evening, where everyone is welcome to gather at a local pub.

• Hood Museum of Art and Rauner Special Collections Library
Explore the main galleries of Dartmouth’s art museum. A special “object study session” is planned to explore polar artifacts from the museum’s collections with a curator. Across the Green, the Rauner Special Collections Library houses a collection of artifacts, diaries, papers, photographs from 19th and 20th century polar expeditions.
• Canoeing on the Connecticut River
Relax on the beautiful Connecticut River, the heart of the Upper Valley. Canoes will be available from the Ledyard Canoe Club boathouse, a student-run organization at the edge of campus. Paddle downriver to explore Gilman Island, swim and cool off in the water, and relax along the shore.
• Appalachian Trail ramble through Hanover
Take an afternoon walk in the woods on the legendary Appalachian Trail. We will be doing 5–7.5 miles of hiking, depending on the interests of the group, on terrain that ranges from easy to moderate. The route crosses the Ordovician Granite of the Lebanon Dome, through wetlands and pine forests, winding up and over the glacially scoured ridges of Velvet Rocks, before descending back to campus.
• Independent excursion
If you do not wish to participate in an organized excursion, you are welcome to join the groups back in town in the evening! The Howe public library and Dartmouth’s Baker–Berry libraries are open to the public and are nice places to get some reading or work done.