Project Grant 2521796
- This $626,859 Project Grant award from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program supports the development of AI-based tools for continental-scale archaeological surveys. The project aims to leverage high-resolution satellite imagery and machine learning models to map abandoned structures and archaeological features across nearly 2 million square kilometers. This will enable researchers to better understand long-term trends in human...
- This $170,992 Project Grant award from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program supports a collaborative research effort led by Brown University to develop AI-based tools for conducting continental-scale archaeological surveys. The key products and services to be delivered under this 3-year award (Aug 2024 - Jul 2027) include: Developing new deep learning models to automatically identify abandoned archaeological structures in...
- This federal Project Grant award from the National Science Foundation (NSF) under the Social, Behavioral, and Economic Sciences (CFDA 47.075) program provides $407,000 to Villanova University to develop a novel, data-driven, AI-enhanced framework for evaluating how physical features of cities shape human well-being, including stress, cognition, and emotional health. The three-phase project will first use machine learning to group neighborhoods by key form characteristics, then conduct controlled...
- This Project Grant award from the National Science Foundation's Biological Sciences (CFDA 47.074) program provides $300,000 to The Ohio State University to develop 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 diverse data sources while preserving data quality, provenance, and attribution. Key deliverables...
- This Project Grant award, in the amount of $302,586, was provided by the National Science Foundation's Social, Behavioral, and Economic Sciences (CFDA 47.075) program. The award funds a research project conducted by Yale University to understand the long-term impacts of neighborhood revitalization policies on individual and family economic outcomes. The project will use existing administrative records and large language models (AI) to systematically analyze thousands of historical documents,...
- This Project Grant award from the National Science Foundation's Biological Sciences (CFDA 47.074) program will provide $867,245 to American University to develop an advanced Artificial Intelligence (AI) and Machine Learning (ML) framework for improving the understanding and prediction of wildland fires. The project aims to create a comprehensive geoscientific dataset by integrating multimodal satellite observations and enable longitudinal data-based fire forecasting. The research will address...
- This $383,941 Project Grant award from the National Science Foundation (CFDA 47.075 Social, Behavioral, and Economic Sciences) supports the development of a collaborative digital platform and research network focused on mapping the historical origins of residential segregation patterns in U.S. urban areas. The key objectives are to create an open-access digital database and GIS mapping resources that enable interdisciplinary research on the locational attainments and household-level...
- This $399,162 Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) aims to develop interpretable, stable, and mass-conserving artificial intelligence (AI) models to improve the computational speed and efficiency of geoscientific models, such as those used for air pollution and climate research. The project will create simpler "surrogate" machine learning models for key components like atmospheric chemistry and wildfire plume rise, allowing for...
- This $500,000 Project Grant was awarded by the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (SBE) program (CFDA 47.075) to the Regents of the University of Minnesota on January 15, 2025. The grant funds the IMOLA (Intelligent Map Recognition Lab) project, which aims to develop advanced computational methods and scientific approaches to extract historical geographic information from scanned maps originally published by the U.S. Geological Survey between 1884 and...
- The National Science Foundation (NSF) awarded a $899,998 Project Grant to The Ohio State University under the Geosciences program (CFDA 47.050) to develop novel artificial intelligence (AI) tools that simulate wetland processes in Earth system models. The three-year project (10/1/2025 - 9/30/2028) aims to create AI models to: 1) integrate mass balance and biochemical kinetics to predict wetland inundation and nutrient transport, 2) simulate wetland flow connectivity using graph neural...
This federal Project Grant award from the National Science Foundation's Social, Behavioral, and Economic Sciences (CFDA 47.075) program provides $450,819 to The Ohio State University to develop artificial intelligence and spatial modeling methods for extracting architectural and geospatial data from historical Sanborn Fire Insurance maps of over 10,000 American municipalities. The project aims to automate the process of digitizing these valuable historical records, which have applications in urban and regional planning but previously lacked efficient data extraction tools. Key innovations include advancing techniques for inferring the three-dimensional structure of buildings and using generative AI to further automate the reconstruction process. The project also provides training opportunities for students and researchers. This award, with a performance period from Oct. 1, 2025 to Sep. 30, 2028, facilitates the creation of longitudinal urban development datasets to support scientific research on the evolution of U.S. cities.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $450.8k | 8/21/25 |