Project Grant 2530448
- 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...
- 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 $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 $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 $597,248 supports research into applying novel approaches to link microbial growth efficiency, function, and energy transfer in the ocean. Funded under the Geosciences program (CFDA 47.050), the award will further understanding of the integrated Earth system through basic research in ocean sciences. Specifically, the University of Miami Rosenstiel School of Marine and Atmospheric Science will conduct research from September 2023 to August 2026 to...
- This $705,374 federal Project Grant was awarded on September 1, 2025 by the National Science Foundation's Geosciences Program (CFDA 47.050) to the University of Maryland Center for Environmental Science (UMCES). The grant will fund a collaborative research project titled "CAIG Deep Learning for Deep Chlorophyll Maxima: Predicting Vertical Distributions of Biogeochemical and Physical Properties". The project aims to leverage satellite data and observations from the Biogeochemical-Argo...
- 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 (NSF), through its Geosciences Program (CFDA 47.050), awarded a $968,427 Project Grant to the University of Washington (UW) to develop the DEEPCYTE, an autonomous underwater flow cytometer designed to detect and monitor phytoplankton populations in marine environments. The key products and services to be delivered under this 3-year grant include: Iterating the DEEPCYTE instrument and buoy platform to a final, smaller and more deployable design Developing automated...
- The University of California San Diego received a $297,994 National Science Foundation Division of Ocean Sciences Project Grant under the Geosciences federal grant program (CFDA 47.050) to conduct research predicting oxygen minimum zone and seasonal microbial activity from community structure using machine learning and novel measurements of ATP turnover. The two-year award beginning September 1, 2021 will support development of new techniques to analyze relationships between microbial...
- This $541,276 Project Grant awarded by the National Science Foundation's Geosciences Program (CFDA 47.050) will fund collaborative research by Oregon State University to develop artificial intelligence (AI) models that leverage gene sequence data to understand ecosystem processes in methane seep habitats. The research will focus on building two new AI models - one that codes genes and classifies them into pathways, and another that uses text and sequence protein representation to identify...
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 detecting ecological changepoints, as well as applying convolutional neural networks for spatial interpolation and predictive mapping of ocean microbial populations and traits. The project aims to streamline oceanographic data analysis, enable model-based rediscovery of ocean provinces, and advance the application of AI and statistics across environmental science disciplines. The funding will support the creation of public-use software packages and cover the project's work from October 1, 2025 through September 30, 2028.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $554.0k | 7/30/25 |