Project Grant 2536664
- This $989,332 Project Grant award from the National Science Foundation (NSF) Biological Sciences program (CFDA 47.074) will develop an advanced artificial intelligence (AI) and machine learning (ML) framework to improve understanding and prediction of wildland fires. The University of Maryland, College Park will integrate multimodal geoscientific data, such as satellite observations, to create a comprehensive dataset for detecting and forecasting wildland fires. The research aims to address...
- The National Science Foundation (NSF) awarded a $889,209 Project Grant under the Geosciences Program (CFDA 47.050) to the University of California, Irvine (UC Irvine) to advance wildfire science, prediction, and management using machine learning. The key products and services to be delivered include: Developing a large new public dataset of fire-related environmental observations to support large-scale machine learning and reproducible research on wildfire spread modeling. Advancing innovative...
- This $2,496,689 Project Grant awarded by the National Science Foundation's Geosciences Program (CFDA 47.050) will establish the FIRE-NET network to develop a new framework for "fast fire risk" across the western United States. The goal is to better understand and predict the growing threat of fast-moving wildfires that have become more frequent and destructive in recent years. The project will leverage expertise across multiple disciplines to create advanced data modeling and...
- The National Science Foundation's Geosciences Program (CFDA 47.050) awarded a $1,000,000 project grant to the University of Illinois on August 1, 2025 for the "EMBER INTELLIGENCE: BUILDING WILDFIRE-RESISTANT COMMUNITIES USING UNMANNED AIRCRAFT SYSTEMS AND DISTRIBUTED DEEP LEARNING" project. The objective is to develop a technological solution called "Ember Intelligence" - a system that uses drone-mounted infrared sensors, edge computing, and artificial intelligence to detect,...
- This $297,813 Project Grant awarded by the National Science Foundation (NSF) under the Integrative Activities program (CFDA 47.083) supports research to advance the predictive understanding of wildfire ignitions in the western United States. The project establishes new collaborations between Boise State University, the Universities Space Research Association, and NASA Ames Research Center to analyze the biophysical, social, and management factors associated with different wildfire ignition...
- This Project Grant award from the National Science Foundation (CFDA 47.050 - Geosciences) provides $735,074 to the University of Washington to develop a Framework for Artificial Intelligence-Enhanced Modeling of Wildfire Geohazards (FAIM-WG). The project aims to create a comprehensive dataset of topographic, meteorological, and environmental variables for major wildfires across the western U.S. This dataset will then be used to develop probabilistic models to predict post-fire debris flow...
- The National Science Foundation awarded a $150,000 Project Grant to the National Center for Atmospheric Research (NCAR) under the Computer and Information Science and Engineering program (CFDA 47.070). The award will support development of a closed-loop sensing, modeling, and communications system to aid in wildfire detection, mapping, and prediction from July 2022 through June 2025. The system aims to leverage detailed 3D environmental models incorporating fuel, terrain, weather and other...
- This federal Project Grant award, totaling $101,562, was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program. The award will fund the development of the LA Fire Knowledge Graph-Agent (LAFIREKG-Agent) platform, an autonomous, end-to-end large language model-based framework designed to enhance situational awareness and support rapid decision-making, predictive modeling, and complex reasoning for wildfire risk...
- This $389,332 federal Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) aims to develop improved computer models and simulation tools to better predict how wildfires spread in areas where forests and natural areas meet cities and towns, known as the wildland-urban interface (WUI). The key objectives are to: 1) Gain a fundamental physical understanding of how fire interacts with individual structures and materials in urban environments at the local...
- The National Science Foundation (NSF) awarded a $430,171 Project Grant under the Engineering program (CFDA 47.041) to Worcester Polytechnic Institute (WPI) to develop a new predictive modeling framework that incorporates canopy biomechanics, aerodynamics, and fire-atmosphere interactions to better understand and predict wildfire behavior in forested areas. The research team will use multi-physics modeling and controlled laboratory experiments to simulate how flexible trees interact with wind and...
This Project Grant award from the National Science Foundation's Biological Sciences Program (CFDA 47.074) will develop an advanced Artificial Intelligence (AI) and Machine Learning (ML) framework to improve the understanding and prediction of wildland fires. The $867,245 grant, awarded to American University, will integrate multimodal geoscientific data from various platforms to create a comprehensive dataset for wildland fire detection and forecasting. The research team will address key computational challenges in large-scale geoscientific data mining and validation of the AI framework. This project aims to provide broad societal and educational benefits through outreach, data dissemination, and curriculum development. It will also engage with federal, state, and local agencies to ensure the developed tools align with operational needs for fire tracking and management.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $867.2k | 8/21/25 |