Project Grant 2426835
- 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 $140,928 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program, awarded on September 1, 2025, supports the development of an open and scalable data infrastructure for AI-enabled ecological and biodiversity research. The project aims to address challenges of fragmented, inconsistent, and inaccessible data by enabling automated, standardized access across multiple data sources while preserving data quality, provenance,...
- 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 Project Grant award from the National Science Foundation's Office of International Science and Engineering (CFDA 47.079) provides $4,500,000 to The Ohio State University to establish the Global Center on AI and Biodiversity Change (ABC). The Center's objectives are to develop AI-enabled solutions for monitoring and understanding climate-induced biodiversity changes, and to support conservation decision-making and policy evaluation. Key focus areas include elucidating species boundaries,...
- The National Science Foundation (NSF) awarded a $100,000 Project Grant under the Biological Sciences (CFDA 47.074) program to The Trustees of Columbia University in the City of New York. The grant, titled "COLLABORATIVE RESEARCH: ACED: PLANET-SCALE AI FOR ACCELERATING ENVIRONMENTAL SCIENCE - INVASIVE SPECIES AND BEYOND," aims to develop a novel artificial intelligence (AI) framework that combines multiple data sources, such as satellite imagery and other unlabeled visual data, to...
- The National Science Foundation (NSF) awarded a $230,552 Project Grant under the Integrative Activities program (CFDA 47.083) to the University of Maine System. The goal of this 2-year grant, with a performance period from January 1, 2025 to December 31, 2026, is to leverage artificial intelligence (AI) to extract information on beetles from imagery generated by the NSF-funded National Ecological Observatory Network (NEON). This effort aims to fuel scientific discovery related to biodiversity...
- The National Science Foundation's Division of Information and Intelligent Systems awarded a $174,827 Project Grant to the University of North Carolina at Charlotte to support research under the Computer and Information Science and Engineering program (CFDA No. 47.070). The award aims to develop deep learning frameworks trained on highly variable biological imaging data to enable accurate and scalable analysis of complex microscopic imagery. Key objectives include exploring deep learning model...
- The National Science Foundation (NSF) awarded a $785,872 Project Grant under its Biological Sciences (CFDA 47.074) Federal Grant Program to the Division of Agriculture of the University of Arkansas. The funding supports the development of an artificial intelligence (AI)-based system for the high-throughput automated identification of ground-dwelling arthropods (insects and other arthropods). The project aims to create tools that can image and classify arthropod specimens, significantly...
- This Project Grant award from the National Science Foundation (CFDA 47.074 Biological Sciences program) provides $850,107 to Ohio University to develop comprehensive artificial intelligence (AI) tools to analyze camera trap images of animals from around the world. The goal is to understand animal coloration and seasonal camouflage mismatch in the context of a rapidly changing planet. The 4-year project will create opportunities for the scientific community to explore a broader set of questions...
- The National Science Foundation (NSF) awarded a $1,199,990 Project Grant under the Computer and Information Science and Engineering (CISE) Federal Grant Program to the University of Oklahoma. The "TREE-CARE: TREEFALL RISK EVALUATION AND EMPOWERMENT FOR COMMUNITY ASSESSMENT AND RESILIENCE ENHANCEMENT" project will develop a science-based, data-driven, and community-centered framework for assessing and managing tree-related hazards in communities. The project will leverage AI-powered...
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 supporting more robust conservation decision-making. The research activities include data and knowledge curation with domain experts, as well as the development and evaluation of the proposed AI/ML approaches. This award reflects NSF's mission to advance scientific discovery and technological innovation, and has been deemed worthy of support through the agency's merit review process.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $169.6k | 4/15/24 |