Project Grant 2530447
- This $554,004 Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) supports a collaborative research project at the University of Washington (UW) to apply statistical neural network models to flow cytometry data in order to reveal the geographical distribution and environmental drivers of ocean microbial ecology. The key objectives are to develop computationally efficient neural network methods for automatically classifying flow cytometry data and...
- The National Science Foundation (NSF) awarded a $536,577 Project Grant under the Geosciences program (CFDA 47.050) to the University of California, Santa Cruz (UCSC) to develop an innovative Artificial Intelligence (AI) system to analyze satellite measurements and high-resolution ocean model outputs. The project aims to detect and measure ocean fronts - boundaries between water masses with different properties - and estimate the heat content of the ocean's upper mixed layer. The researchers plan...
- 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...
- This National Science Foundation (NSF) Project Grant award under the Geosciences Program (CFDA 47.050) provides $612,291 to the University of California, Davis (UC Davis) to develop a sophisticated artificial intelligence (AI) system to analyze satellite measurements and high-resolution ocean model outputs. The goal is to detect and measure ocean fronts, which are boundaries between water masses with different properties, and estimate the heat content of the ocean's upper mixed layer. The...
- This $374,799 Project Grant awarded by the National Science Foundation's Geosciences Program (CFDA 47.050) supports collaborative research by the University of Maryland Baltimore County (UMBC) to leverage satellite data and autonomous ocean sensors to develop deep learning models that can predict vertical distributions of biogeochemical and physical properties, including phytoplankton biomass, nutrient limitation, and net primary production below the ocean surface. The research aims to address...
- This Project Grant award for $529,636 from the National Science Foundation's Geosciences Program (CFDA 47.050) will enable the University of Louisiana at Lafayette to develop innovative artificial intelligence methods to analyze hyperspectral satellite imagery and construct a large-scale database to better understand phytoplankton community dynamics in coastal waters. The key products and services to be delivered include: Establishing a comprehensive database of phytoplankton observations to...
- This $714,230 Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) will fund the development of a multiscale AI emulator to investigate complex nonlinear dynamics of the ocean circulation and bridge the gap between understanding and simulating ocean variability across multiple time and space scales. The primary objectives are to construct a 3D physically-based AI ocean emulator from heterogeneous datasets, evaluate the multiscale emulator, and determine...
- This National Science Foundation Project Grant of $524,000 will support the development of network-based models to evaluate functional biodiversity responses to climate change and species invasions in marine biological communities. Funded under the Biological Sciences program (CFDA 47.074), this award reflects NSF's mission to promote biological sciences research and strengthen the scientific enterprise. Specifically, researchers at the University of California, Davis will leverage long-term...
- This federal Project Grant award, valued at $745,396.00 and provided by the National Science Foundation's Geosciences Program (CFDA 47.050), supports collaborative research to investigate the large-scale nutritional ecology of diverse phytoplankton species in the ocean. The research aims to identify biomarkers that indicate nutrient stress in various phytoplankton groups, and to map nutrient stress states across multiple geographic regions. This work leverages a funded GO-SHIP cruise,...
- This $586,557 federal Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) supports a collaborative research initiative to develop artificial intelligence (AI) models that can leverage gene sequence data to better understand ecosystem processes, with a focus on methane seep habitats. The project will collect new microbial samples from methane seeps off the coasts of Oregon and Washington and employ novel natural language processing AI approaches to predict...
This National Science Foundation (NSF) Geosciences program (CFDA 47.050) Project Grant award of $592,981 to the University of California, Santa Cruz (UCSC) will support a collaborative research project focused on using statistical neural networks to analyze flow cytometry data to reveal the geographical distribution of phytoplankton and how the environment shapes these patterns. The project will develop computationally efficient neural network models to automatically classify cell-level data with environmental covariates, enabling more streamlined analysis and revealing biological responses to changing environments. Generative neural networks will also be used for changepoint detection to identify shifts in phytoplankton communities, and convolutional neural networks will be applied to density regression and spatial interpolation of flow cytometry data to predict complete cytogram images beyond cruise track locations. The resulting methodologies and public-use software packages are expected to advance AI and statistics, data science, and oceanography, while also being broadly applicable across environmental science, ecology, agriculture, epidemiology, and econometrics disciplines that deal with complex high-dimensional dependent data. The award period runs from October 1, 2025 to September 30, 2028.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $593.0k | 7/30/25 |