Groundbreaking Research on Wildfire Spread

NFPA announced that the article “Recurrent Convolutional Deep Neural Networks for Modeling Time-Resolved Wildfire Spread Behaviour”…
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The National Fire Protection Association® (NFPA®) announced that the article “Recurrent Convolutional Deep Neural Networks for Modeling Time-Resolved Wildfire Spread Behaviour” was awarded the 2024 Harry C. Bigglestone Award. This prestigious award is given annually to the paper appearing in the journal Fire Technology that best represents excellence in communicating fire protection concepts. The award is accompanied by a $5,000 cash prize from NFPA.

The presentation of the Harry C. Bigglestone Award and recognition of the paper’s authors, John Burge, Matthew Bonanni, Lily Hu, and Matthias Ihme, took place at the NFPA Stars at Night awards ceremony during the annual NFPA Conference & Expo® (C&E) in Orlando on Sunday, June 16, 2024.

The researchers’ use of advanced machine learning techniques to create a model that predicts wildfire spread with significant accuracy was highlighted as exemplifying the power of technology and science in solving real-world fire and life safety problems. The award recipients were honored for their dedication, curiosity, research advancing the field of fire science, and working to ensure that communities are better prepared to protect lives and property from the devastating impacts of wildfires.

Award Recipients:

  • John Burge works at Google Research, where he has dedicated his efforts to applying deep neural networks to predict wildfire dynamics and propagation. With Google since 2007, he has leveraged machine learning to address various challenges, including behavioral modeling of users engaged with mobile applications and weather forecasting.
  • Matthew Bonanni is a PhD candidate in mechanical engineering, advised by Professor Matthias Ihme. He is a NASA Fellow, and his PhD research focuses on the simulation of turbulent, reacting fluid flows.
  • Lily Hu is a researcher and engineer with Google Research. She conducted research in machine learning for engineering systems, physical sciences, and sustainability, drawing upon computer vision, decision analysis, and optimization.
  • Dr. Matthias Ihme is a professor in the Department of Mechanical Engineering at Stanford and the Department of Photon Science at the SLAC National Accelerator Laboratory. His research interests broadly focus on the computational modeling of reacting flows, developing numerical methods, and investigating advanced energy conversion concepts and molecular processes.

The 2024 NFPA Stars at Night Gala celebrated 14 individuals or organizations across seven award categories. You can learn more about this year’s recipients by visiting the awards section of the NFPA website.

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