Project Grant 2530984

Award Date 11/1/25
Completion Date 10/31/28
Dollars Obligated $900K
Federal Grant Program
47.050
Assistance Type
Project Grant
Place of Performance
Princeton, NJ 08544, USA
Similar Awards
This $589,708 Project Grant award from the National Science Foundation's Geosciences program (CFDA 47.050) supports research to advance artificial intelligence (AI) methods for imaging and monitoring the Earth's subsurface. The project aims to develop a multi-task deep learning inversion framework that can simultaneously estimate subsurface velocity structures and earthquake source parameters using passive seismic data. By integrating deep learning with conventional full-waveform inversion...
The National Science Foundation (NSF) awarded a $757,763 Project Grant under the Geosciences program (CFDA 47.050) to Carnegie Mellon University (CMU) to develop a new artificial intelligence (AI) framework for analyzing hyperspectral data to map ore deposits. The project, titled "COLLABORATIVE RESEARCH: CAIG: MAPPING ORE DEPOSITS WITH ARTIFICIAL INTELLIGENCE (MODAI)", will leverage advanced hyperspectral remote sensing techniques and AI to improve the identification of critical...
This Project Grant award for $441,467 from the National Science Foundation (NSF) Geosciences Program (CFDA 47.050) supports the development of a new artificial intelligence (AI) framework to analyze hyperspectral data for mapping ore deposits. The project, titled "Collaborative Research: CAIG: Mapping Ore Deposits with Artificial Intelligence (MODAI)," aims to improve the effectiveness of hyperspectral mineral mapping to accelerate the identification of critical mineral resources....
This $599,999 project grant awarded by the National Science Foundation's Geosciences Program (CFDA 47.050) aims to develop an affordable and scalable cyber-infrastructure for reconstructing the 3D morphology of foraminifera shells from 2D microscope images. The infrastructure will leverage robotic imaging devices and artificial intelligence to create an accessible platform for scientists, students, and citizen scientists to study these tiny marine organisms, which have a rich fossil record....
This Project Grant award from the National Science Foundation (CFDA 47.050 Geosciences Program) provides $452,604 to President and Fellows of Harvard College to develop a foundational AI model for advanced seismic data analysis. The project aims to revolutionize earthquake science by using AI to identify patterns in seismic data and gain a deeper understanding of earthquake characteristics. The model will be trained on a vast archive of seismic data to improve earthquake detection, localization,...
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 federal Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) provides $193,567 to the University of Texas at Dallas (UTD) to advance artificial intelligence (AI) methods for imaging and monitoring the Earth's subsurface. The research team will develop a multi-task deep learning inversion framework that simultaneously estimates subsurface velocity structures and earthquake source parameters using passive seismic data. This unified framework aims to...
This Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) provides $300,001 to Trustees of Boston University to develop a foundational Artificial Intelligence (AI) model for advanced seismic data analysis to improve earthquake detection, localization, and characterization. The project aims to revolutionize earthquake science by using AI to unravel patterns in seismic data, leading to more accurate tools for earthquake monitoring and potential prediction....
This Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) provides $650,000 over a 3-year period to the University of Southern California to develop an AI model that can better understand fault dynamics and earthquake hazards in heavily faulted geologic basins. The project builds a multiphysics fault network model to discover reduced-order governing equations for the evolution of stress in complex fault systems, using the Southern Permian Basin in the...
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 Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) provides $899,999.00 to Princeton University to develop new artificial intelligence (AI) technologies that can automatically analyze images of rock cross-sections. The goal is to accelerate scientific discovery and improve reproducibility in geoscience research.

The project will address the challenge of limited training data by creating a large volume of labeled synthetic data for rock cross-sections using computer graphics and physics-based simulation techniques. These synthetic data will be used to pre-train foundation AI models, which can then be fine-tuned with a small number of real rock images to perform visual analysis tasks. As a case study, the project will apply the new AI capabilities to investigate the role of the rise of metazoan reefs in the coevolution of animals and their environments during the Cambrian radiation, using an extensive field collection from South Australia. The award integrates the research with undergraduate, graduate, and K-12 outreach activities.

Generated 8/5/25, 5:53 AM