Project Grant 2344690
- Federal Grant Award Summary The National Science Foundation's Division of Polar Programs (CFDA 47.078) awarded $738,807 to The Leland Stanford Junior University effective September 1, 2025, through August 31, 2030, to develop physics-informed deep learning algorithms for modeling ice sheet and ice shelf dynamics. The primary deliverable is DIFFICE.JAX, an open-source deep learning tool designed to infer continent-wide ice shelf viscosity structures from satellite data. This technology...
- Federal Project Grant Award Summary The National Science Foundation (NSF), through its Computer and Information Science and Engineering program (CFDA 47.070), awarded The Leland Stanford Junior University a $300,000 project grant effective September 1, 2026, through August 31, 2029. The project develops DIFFICE-JAX 2.0, an open-source community cyberinfrastructure platform that combines artificial intelligence with high-fidelity physics models to infer hidden physical properties of Antarctic ice...
- Federal Project Grant Summary The University of Pennsylvania received $153,965 in federal funding under the National Science Foundation's Polar Programs (CFDA 47.078) for a collaborative U.S.-U.K. research initiative titled "Understanding Surface-to-Bed Meltwater Pathways Across the Greenland Ice Sheet Using Machine-Learning and Physics-Based Models." The award, effective October 1, 2025 through January 31, 2027, was jointly funded by NSF's Directorate for Geosciences and the United...
- The Leland Stanford Junior University was awarded a $163,981 Project Grant from the National Science Foundation Division of Polar Programs under the Polar Programs federal grant program (CFDA 47.078). The grant will fund collaborative research to investigate four decades of subsurface change beneath the Ross Ice Shelf in Antarctica using historical and modern radar sounding data. The research aims to strengthen fundamental understanding of the polar regions by expanding knowledge of ice shelf...
- The National Science Foundation Division of Polar Programs awarded a $245,046 Project Grant to Stanford University under the Polar Programs federal grant program (CFDA 47.078) to develop and field test community-driven ice penetrating radar systems for observing complex ice sheet structure and flow. Specifically, the award will support developing a snowmobile-towed radar and unmanned aerial vehicle radar system based on shared software and post-processing tools. Both systems are designed to...
- The National Science Foundation awarded a $269,223 Project Grant to the University of Texas at Austin from the Polar Programs federal grant program (CFDA 47.078) to support research titled "Collaborative Research: Machine-Enabled Modeling of Terminus Ablation for Greenland's Outlet Glaciers." The research aims to improve projections of sea-level rise from Greenland through developing physics-based modeling of ice-ocean interactions at outlet glaciers using machine learning analysis...
- The National Science Foundation's (NSF) Division of Polar Programs awarded $684,964 under the Polar Programs federal grant program (CFDA 47.078) to Stanford University. The five-year project grant funding will support research and development of customized numerical models to understand the possibility and implications of an internal shear band forming in ice flowing over rough topography. Specifically, the principal investigator will develop a suite of open-source tools to test the hypothesis...
- Federal Grant Award Summary The Trustees of Dartmouth College, through its Office of Sponsored Projects, received a $505,036 Project Grant from the National Science Foundation (NSF) Geosciences program (CFDA 47.050) effective January 1, 2026, through December 31, 2028, to develop physics-informed machine learning models for predicting ice sheet dynamics. The primary deliverable is an extension of the open-source Physics Informed Neural Networks for Ice and Climate (PINNICLE) framework to...
- The National Science Foundation awarded a $2.8 million project grant under the Geosciences program (CFDA 47.050) to Virginia Polytechnic Institute and State University for the period of October 1, 2022 to December 31, 2026. The project aims to map changes in Greenland resulting from ice thinning and explore emerging landslide and hazard risks. Researchers will integrate local observations from Greenlandic communities with remote sensing data to understand how hazards evolve over time. Advanced...
- Federal Grant Award Summary The National Science Foundation's Division of Polar Programs (CFDA 47.078) awarded $782,557 to The Research Foundation for the State University of New York on August 1, 2025, for a CAREER project addressing dimensionality reduction of glacier and ice-sheet processes using deep learning. The primary deliverable is the development and evaluation of three high-efficiency artificial intelligence (AI)-based modules that represent complex glacier processes for integration...
This $411,096 federal Project Grant award was provided by the National Science Foundation's Polar Programs (CFDA 47.078) to The Leland Stanford Junior University (Stanford University). The project aims to utilize machine learning and physics-based models to map and understand how surface meltwater on the Greenland ice sheet reaches the bedrock, which can impact ice sheet dynamics and response to climate change. Key products and services to be delivered include: The award period runs from October 1, 2023 to January 31, 2026. This project aims to enhance the glaciology community's ability to analyze satellite imagery and model ice sheet hydrology, ultimately improving understanding of ice sheet responses to climate change.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $411.1k | 11/21/23 |