معرفی
Ryan Johnson is an Assistant Professor in the Civil & Environmental Engineering Department at the University of Utah. His research focuses on integrating machine learning and open-source software into hydrological modeling, particularly in snow distribution, water supply forecasting, and low-cost snow monitoring systems. He teaches courses in Hydraulics, Data Science, and Hydroinformatics.
Current research projects include:
- Deep neural networks for heterogeneous snow modeling in the Western US.
- LSTM-based extensions of the National Water Model to season-to-season forecasts.
- Low-cost snow monitoring systems for critical water supply catchments.
He has secured grants from institutions like the University of Alabama, U.S. Geological Survey, and National Oceanic and Atmospheric Administration, totaling over $1.2M in funding since 2023. His work emphasizes climate-resilient water management, with a focus on urban flooding, water quality, and adaptive infrastructure strategies.
Recent publications span topics like real-time urban drainage control, climate-sensitive water demand modeling, and the Great Salt Lake's declining resilience. Johnson collaborates widely, with co-authors from institutions such as MIT, NOAA, and the University of Utah’s Department of City & Metropolitan Planning.
