This Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) provides $462,400 to the University of California San Diego, Scripps Institution of Oceanography, to develop advanced machine learning techniques for generating realistic, synthetic earthquake ground motion simulations. The goal is to create a faster, more generalizable physics-based model that can efficiently study large, infrequent earthquakes and assess their hazards for California and Nevada....
This National Science Foundation (NSF) Geosciences Program (CFDA 47.050) Project Grant award of $249,272, effective January 1, 2026 through December 31, 2028, supports the development of machine learning techniques to generate realistic, synthetic ground motion simulations for studying large earthquakes. The project, conducted by the University of Nevada, Reno (UNR), aims to create a physics-based, parametric surrogate model called Operator Inference (OPINF) that can produce seismic ground...
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 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 awarded a $303,820 Project Grant under the Geosciences program (CFDA 47.050) to the University of California, Santa Cruz to characterize the seismic radiation from finite earthquake sources and investigate its links to fault physics. The research aims to improve understanding of large earthquake scenarios in different tectonic plate boundary settings by developing physics-based computational models that can reproduce geophysical observations. Key objectives...
This $125,000 Project Grant award from the National Science Foundation's (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences (CFDA 47.049) program will support research at the University of Texas at Austin to develop a Bayesian inference framework for learning earthquake cycle deformation processes across scales. The project aims to create an advanced framework capable of assimilating multi-modal observational data into high-resolution forward models to infer...
The National Science Foundation's (NSF) Office of Advanced Cyberinfrastructure awarded a $740,000 Project Grant to the University of California, San Diego (UCSD) to develop the QUAKEWORX software framework. This framework will enable a wide community of users to access state-of-the-art physics-based models for forecasting and simulating earthquakes, earthquakes ruptures, and seismic hazards. The project, funded through the NSF's Computer and Information Science and Engineering (CISE) program,...
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 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 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...