Project Grant 2548082
- The National Science Foundation Division of Ocean Sciences awarded Woods Hole Oceanographic Institution $699,975 on August 1, 2026, under the Geosciences program (CFDA 47.050) to develop a physics-informed artificial intelligence method for estimating seafloor topography in coastal surf zones using remotely sensed drone imagery and surface current observations. The research addresses the limitation that accurate seafloor depth measurements are difficult to obtain during coastal storms, which...
- The National Science Foundation Office of Integrative Activities awarded Northeastern University $435,082 on October 1, 2026, under the Geosciences program (CFDA 47.050) to develop artificial intelligence tools that estimate nearshore bathymetry, waves, and currents from remote sensing data. The project, titled "Collaborative Research: CAIG: Transforming Understanding and Prediction of Nearshore Processes via AI-Powered Simultaneous Mapping of Bathymetry, Waves, and Currents," will...
- The National Science Foundation Office of Integrative Activities awarded Texas A&M University $340,975 on October 1, 2026, under the Geosciences program (CFDA 47.050) to develop physics-informed artificial intelligence tools that estimate nearshore bathymetry, waves, and currents from remote sensing data. The project creates a physics-informed, remote-sensing-driven and AI-powered modeling (PRAM) system combining deep learning with physical constraints from wave mechanics to produce...
- The National Science Foundation Office of Integrative Activities awarded North Carolina State University $800,013 on October 1, 2026, for a collaborative research project applying physics-informed deep learning to understand and predict coastal hypoxia formation mechanisms, particularly the summer dead zone along the Louisiana-Texas shelf. The project develops a multi-architecture physics-informed neural network framework integrating U-Net and DeepLabV3+ semantic-segmentation networks to map...
- The University of Minnesota will receive $446,973 from the National Science Foundation under the Geosciences program (CFDA 47.050) to conduct experimental and numerical studies of bubble entrainment by breaking waves from October 1, 2022 to September 30, 2025. The research aims to advance understanding of the physical processes controlling bubble generation and dispersal in ocean waves and their dependence on factors like wave scale, slope, wind forcing, and salinity. Researchers will leverage...
- The National Science Foundation Division of Information and Intelligent Systems awarded a $945,291 Project Grant to the Regents of the University of Minnesota under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The three-year award running from January 1, 2023 to December 31, 2026 will support research to develop novel capabilities for autonomous underwater robotic perception and navigation. Specifically, the university researchers will work to enhance...
- Federal Grant Award Summary The National Science Foundation's Office of Integrative Activities awarded $871,084 to Woods Hole Oceanographic Institution under the Geosciences program (CFDA 47.050) effective October 1, 2025, through September 30, 2028. This collaborative research project develops an innovative observing system that integrates artificial intelligence with multiple autonomous underwater vehicles (AUVs) to characterize three-dimensional flow structures in tidally-driven coastal...
- The National Science Foundation (NSF) awarded a $320,000 Project Grant under the Geosciences Program (CFDA 47.050) to the University of Delaware. The funding will support collaborative research to empower artificial intelligence (AI) to reveal phytoplankton community dynamics in coastal oceans. The project aims to address the scarcity of in-situ data for estuarine-coastal phytoplankton by constructing a large-scale database of phytoplankton observations, enabling global data sharing. It will...
- The National Science Foundation Office of Integrative Activities awarded the University of Rhode Island $332,242 on January 1, 2027, to develop artificial intelligence–powered tools that predict marine snow composition from underwater imagery, with performance through December 31, 2029, under the Geosciences program (CFDA 47.050). The project addresses the gap between camera-based particle detection and compositional analysis of sinking marine particles. Researchers will build an interpretable...
- The National Science Foundation Office of Integrative Activities awarded Massachusetts Institute of Technology $898,723 on September 1, 2026, under the Geosciences program (CFDA 47.050) to develop artificial intelligence tools that combine physics-based models with high-resolution topographic data to forecast landscape evolution and erosion. The project will construct a hybrid simulation-to-real framework in which physics-informed generative AI models trained on landscape evolution simulations...
The National Science Foundation Division of Ocean Sciences awarded the Regents of the University of Minnesota $648,690 on August 1, 2026, under the Geosciences program (CFDA 47.050) to develop physics-informed artificial intelligence methods for estimating seafloor topography in coastal surf zones using drone-based camera imagery and surface flow observations. The project addresses a critical gap in measuring seafloor depth during and after coastal storms, where rapid morphological change limits understanding of coupled hydrodynamic and sediment transport processes. The research team—comprising physical oceanographers, AI experts, and numerical modelers—will build a deep learning model trained on state-of-the-art numerical simulations across wave and bathymetric conditions representative of beaches worldwide. The AI approach will process remotely sensed, spatially dense surface current data to infer bathymetry, with validation against observed seafloor evolution during storm events. Numerical simulations will generate additional training data and support testing of hypotheses linking oblique wave energy, alongshore flows, and surf zone morphological response. Deliverables include the validated AI models and accompanying code, which will enable coastal managers and communities to better predict storm impacts on beaches, dunes, and infrastructure. The project incorporates student training and includes collaborative development across multiple disciplinary teams. Work is performed at the University of Minnesota, Minneapolis, with a period of performance from August 1, 2026, through July 31, 2029.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $648.7k | 7/28/26 |