Researchers are trying to understand why some wild species do better than others over time, as the environment changes.

Jane Housley, a BYU mathematics graduate and wildfire modeling researcher, developed a faster, smarter way to predict how wind moves through fire-prone terrain. Her work could help firefighters ...

Researchers applied the mathematical theory of synchronization to clarify how recurrent neural networks (RNNs) generate predictions, revealing a certain map, based on the generalized synchronization, ...

Using machine learning and math, a Brigham Young University student improved a key tool firefighters rely on during wildfire season As Utah enters the heart of wildfire season, wind might be the most ...