Project Grant 2531922
- This $198,141 project grant awarded by the National Science Foundation's Biological Sciences program (CFDA 47.074) seeks to enhance predictive understanding of global species distributions through the development of advanced generative artificial intelligence (AI) models. The project aims to create a versatile foundation model that can be used by scientists, conservationists, and educators to better understand and protect the natural world. By training this model on a vast array of environmental...
- This $240,000 Project Grant awarded by the National Science Foundation's Computer and Information Science and Engineering (CFDA 47.070) program supports research to develop advanced computer vision (CV) approaches for global biodiversity monitoring. The project aims to: (1) robustly identify rare, visually similar, and novel categories of biodiversity data using augmented training data and active curation; (2) adapt CV models to new deployments and identify valuable data for specialized tasks;...
- This Project Grant award, valued at $100,000.00 and provided by the National Science Foundation (NSF) Biological Sciences (CFDA 47.074) Federal Grant Program, supports a collaborative research project titled "ACED: Planet-Scale AI for Accelerating Environmental Science - Invasive Species and Beyond." The research aims to develop a novel AI framework that combines multiple data sources, including satellite imagery and other visual data, to automatically discover interpretable scientific...
- This federal Project Grant award, provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program, aims to develop transformative new wireless communication and artificial intelligence (AI) tools for automating biodiversity data collection, processing, and analysis. The $598,865 grant, awarded to Duke University, will fund the creation of probabilistic models to account for errors in inferring species composition from audio,...
- This $923,098 federal Project Grant award from the National Science Foundation (NSF) Biological Sciences program (CFDA 47.074) aims to strengthen global biodiversity research by building informatics capacity for ancient environmental DNA (aDNA) analysis. The grant will enable the integration of aDNA data into an open data ecosystem and establish a governance framework and social infrastructure to ensure high-quality, interoperable aDNA data and analytics. Specifically, the project will extend...
- This $493,248 federal Project Grant award from the National Science Foundation's Biological Sciences program (CFDA 47.074) will enable the integration of ancient environmental DNA (aDNA) data into a linked open ecosystem of paleoecological and bioinformatic resources. The project will build the advanced data platforms and social infrastructure needed to support global-scale biodiversity research at unprecedented taxonomic resolution, coverage, and temporal extent. Key activities include...
- This Project Grant award for $600,000 from the National Science Foundation's (NSF) Biological Sciences program (CFDA 47.074) will fund the development of an interactive web-based platform called OpenForest4D. This platform will enable the generation of high-quality, research-grade estimates of forest structure and above-ground biomass across large spatial and temporal scales by applying novel statistical and AI models to a fusion of multi-source remote sensing data. The University of Florida...
- The National Science Foundation (NSF) awarded a $169,618 Computer and Information Science and Engineering (CFDA 47.070) Project Grant to Oklahoma State University (OSU) to develop artificial intelligence (AI) and machine learning (ML) techniques that provide novel insights into the extinction risk of biological species. The project aims to leverage natural language processing and automated reasoning to address challenges in biodiversity data and species taxonomy classification, ultimately...
- This Project Grant award, valued at $1,018,281 and provided by the National Science Foundation's Office of Advanced Cyberinfrastructure, supports the development of OpenForest4D - a web-based cyberinfrastructure platform for next-generation 4D forest mapping and monitoring. The goal is to apply novel statistical models and artificial intelligence methodologies to a fusion of multi-source remote sensing data to generate on-demand, research-grade estimates of forest structure and above-ground...
- 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 $300,000 Project Grant award from the National Science Foundation's Biological Sciences (CFDA 47.074) program will develop an open and scalable data infrastructure to enable AI-enabled ecological and biodiversity research. The infrastructure will address challenges of fragmented, inconsistent, and inaccessible data by automating standardized access across various data sources while preserving data quality, provenance, and attribution. This 3-year project will create a dynamic inventory and map of existing data sources, define shared schemas, align taxonomies and ontologies, and provide standard machine-accessible interfaces. The infrastructure will be evaluated using exemplar use cases spanning multiple stakeholders to serve as a foundation for AI-driven discoveries and action in ecology and related fields.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $300.0k | 8/18/25 |