Project Grant 2530752
Award Date
9/1/25
Completion Date
8/31/28
Dollars Obligated
$758K
Federal Agency
Office of Integrative Activities
Federal Grant Program
47.050
Assistance Type
Project Grant
Place of Performance
Pittsburgh, PA 15213, USA
Similar Awards
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....
The National Science Foundation (NSF) awarded a $274,361 Project Grant under the NSF Technology, Innovation, and Partnerships (CFDA 47.084) program to Terra AI, Inc., a for-profit company based in Sunnyvale, CA. The award period is from September 1, 2024 to August 31, 2025. The grant will fund the development of AI systems and methods to accelerate the discovery and extraction of critical natural resources such as copper, nickel, cobalt, and rare earth minerals. The project aims to improve...
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...
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...
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 $200,000 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program will enable Carnegie Mellon University (CMU) to develop advanced spatiotemporal foundation models and generative AI capabilities for large-scale multimodal threat detection. The project aims to create new data representations and neural network architectures to scale up existing spatial detection algorithms, enabling the rapid deployment of analytical...
This $126,270 federal Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) aims to develop new capabilities to monitor and understand forest carbon dynamics in the Earth system. The key products and services to be delivered include: Cross-platform and cross-region learning frameworks to enable fine-scale carbon dynamics monitoring at large geographic scales. High-fidelity fast approximations of theory-based carbon forecasting models using new meta-learning...
This National Science Foundation (NSF) Project Grant under the Geosciences program (CFDA 47.050) will provide $392,914 to Carnegie Mellon University (CMU) from October 1, 2024 to September 30, 2027 to develop a collaborative research project titled "CAIG: Next Generation Machine-Learning Approach to Decode High-Resolution Earthquake Catalogs." The project aims to leverage advanced machine learning models and algorithms to gain deeper insights into earthquake dynamics and improve...
This $207,737 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will fund research to develop a new class of machine learning models called "Programmatic Foundation Models" that can efficiently analyze large-scale satellite, aerial, and ground imagery. The goal is to create interpretable, robust AI models that can understand global and local phenomena from images, providing insights...
This Project Grant award of $213,433.00 from the National Science Foundation's (NSF) Integrative Activities program (CFDA 47.083) supports a six-month fellowship to enhance the lead researcher's career trajectory in data science and geoinformatics at the Carnegie Institution for Science in Washington, DC. The primary goals are to establish a reusable methodology for efficiently deploying data science in geoscience studies to accelerate scientific discoveries, with a focus on mineralogy. The...