Project Grant 2525871
- The National Science Foundation's Geosciences Program (CFDA 47.050) awarded a $319,877 Project Grant to The Trustees of Columbia University in the City of New York to investigate seismogenesis and faults in Eastern North America. The project aims to develop new machine-learning and cross-correlation methods to detect previously undetected low-magnitude earthquake events, generating a high-resolution, deep-magnitude earthquake catalog for the region. This expanded seismic data is expected to...
- This National Science Foundation (NSF) Project Grant award under the Geosciences Program (CFDA 47.050) provides $299,539 to the Georgia Tech Research Corporation to develop advanced machine learning models and algorithms to study the intricate dynamics of earthquakes. The key objectives are to uncover precursory signals that may precede major seismic events, enhance earthquake forecasting capabilities, and create open-source tools accessible to researchers and practitioners worldwide. The...
- This federal Project Grant award of $386,220, provided by the National Science Foundation's Geosciences Program (CFDA 47.050), supports the development of machine learning techniques to efficiently generate realistic, synthetic earthquake ground motions. The research, conducted by the University of California, San Diego, aims to enable geologists to effectively study large earthquakes and assess the hazards they pose to California and Nevada. The project will produce publicly available...
- This National Science Foundation (NSF) Project Grant award under the Geosciences program (CFDA 47.050) supports a collaborative research project between the University of California, Santa Cruz (UCSC) and Hebrew University to directly measure fault rupture dynamics and seismic wave propagation in a laboratory setting. The $399,601 award, effective from August 1, 2024 to July 31, 2027, will leverage specialized laboratory equipment to conduct high-speed imaging and in-situ seismogram...
- 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...
- The National Science Foundation (NSF) awarded a $462,400 Project Grant under the Geosciences Program (CFDA 47.050) to the University of California San Diego's (UCSD) Scripps Institution of Oceanography. This collaborative research project aims to develop machine learning techniques to efficiently generate realistic, synthetic ground motion data for the study of large, infrequent earthquakes in California and Nevada. The research will create parametric surrogate models of seismic ground motions...
- This National Science Foundation (NSF) Geosciences Program (CFDA 47.050) project grant award of $122,773 to the San Diego State University Research Foundation will support collaborative research to identify earthquake-related damage preserved in fault zones and use this information to better assess potential earthquake hazards along known fault lines. The research, which will run from June 2025 to May 2028, aims to develop criteria to distinguish earthquake-related damage from long-term fault...
- This National Science Foundation (NSF) Geosciences program (CFDA 47.050) award of $249,272 to the University of Nevada, Reno (UNR) supports the development of machine learning techniques to generate realistic, synthetic earthquake ground motion simulations. The goal is to enable geologists to efficiently study large, infrequent earthquakes and assess their hazards to California and Nevada. The project will create publicly available software and educational resources to train future scientists...
- 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 $175,000 Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) supports research to develop an AI model for understanding fault dynamics and earthquake hazards in complex fault networks. The project, led by the California Institute of Technology (Caltech), aims to build a multiphysics fault network model to discover reduced-order governing equations for the evolution of stress in fault systems. This work will enable improved assessment of regional...
This $139,058 Project Grant awarded by the National Science Foundation's Geosciences Program (CFDA 47.050) will fund collaborative research to investigate seismogenesis and faults in Eastern North America. The project aims to significantly improve and expand catalogs of earthquake parameters in the region by applying advanced machine learning and cross-correlation techniques to detect previously undetected earthquake events at lower magnitude thresholds and higher location precision. The enhanced earthquake catalog data will illuminate active faults at depth and provide new insights into seismogenesis and seismotectonics in this stable continental region, which faces earthquake hazard risk despite its low seismicity rates. The project will be conducted by the University of California, Berkeley and is set to run from September 1, 2025 through August 31, 2027.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $139.1k | 8/20/25 |