The National Science Foundation (NSF) Directorate for Engineering has awarded a $391,951 Project Grant to The Johns Hopkins University to develop a novel system for rapidly and accurately assessing cascading seismic hazards and impacts using satellite imagery and causal modeling. The project, funded under the NSF Engineering program (CFDA 47.041), aims to integrate satellite data with existing geophysical and structural fragility models to jointly estimate the occurrence and location of...
This National Science Foundation (NSF) Engineering program (CFDA 47.041) Project Grant, awarded on June 1, 2024 for $499,929.00, will support research to improve forecasting and mitigation of disaster impacts by leveraging advances in language models and examining the universality and heterogeneity of post-disaster mobility behavior. The primary awardee, New York University (NYU), will develop a data governance mechanism - a "data commons platform" - to enable inclusive access and...
This $911,306 federal Project Grant award from the National Science Foundation's (NSF) Integrative Activities (IA) program, CFDA 47.083, supports the development of a comprehensive system to detect and map natural disasters using deep subspace learning techniques on multi-band and multi-spectral satellite imagery. The project aims to enable real-time monitoring and accurate identification of areas affected by natural events such as flooding, wildfires, earthquakes, and landslides. It will...
This National Science Foundation (NSF) Project Grant award under the 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. The project aims to revolutionize earthquake science by using AI to unravel patterns in seismic data, improving earthquake detection, localization, and characterization. The research will involve developing specialized neural network modules and...
This $674,291 federal Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) supports research to enhance the understanding of landslide causality through the integration of artificial intelligence (AI) and machine learning (ML) technologies with established geoscientific domain knowledge.
The research will pursue four key thrusts: (1) establishing and annotating datasets and benchmarks for landslide causality analysis; (2) developing AI-physics hybrid...
This $284,443 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will support the development of AI emulator tools for estimating the statistics of rare climate events, such as heat waves and cold snaps. The University of Chicago, the awardee, will leverage AI techniques, including AI dynamic Galerkin approximation and rare-event sampling, to enhance the training and usefulness of AI emulators...
This $100,000 Project Grant award is funded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070). The award supports a research project at the University of Oklahoma's Office of Research Administration that aims to expand on earlier work by the research team to identify, measure, and address multiple ways that artificial intelligence (AI) could be inadvertently misused within environmental and Earth sciences...
This $500,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research and development to enhance climate resilience and confront coastal hazards in the Great Lakes region.
The project, led by Michigan Technological University, combines natural hazard research with local knowledge to create practical tools and strategies to help rural, remote, and indigenous communities in the region...
The Trustees of Columbia University in the City of New York received a three-year, $599,998 Project Grant award from the National Science Foundation Office of Advanced Cyberinfrastructure to develop open-source cyberinfrastructure as a decision engine for socioeconomic disaster risk assessment and modeling. The grant falls under the Foundation's Computer and Information Science and Engineering program (CFDA #47.070), which supports investigator-initiated research and education across...
This $299,524 award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) federal grant program (CFDA 47.070) will support The Johns Hopkins University in developing an innovative artificial intelligence (AI)-integrated framework to enhance the efficiency and accessibility of exascale multiphysics simulations. The project aims to enable rapid parameter space exploration at unprecedented scales by integrating advanced AI techniques with...
This federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will provide $589,274 to The Johns Hopkins University to develop a next-generation scalable, efficient, and transparent causality-informed probabilistic AI infrastructure. This cyberinfrastructure will enable joint modeling and assessment of cascading disaster impacts from natural hazards like earthquakes and hurricanes, assisting emergency management and enhancing community resilience. The project aims to advance modeling, integration, and inference of complex causal Bayesian networks to support real-time spatial probability estimates of multiple disaster impacts. Additionally, it will integrate research, education, training, and outreach activities to foster interest in computational and interdisciplinary science, raise awareness of natural hazard impacts, and facilitate workforce development. The award period spans January 1, 2025 to December 31, 2029.