My research develops mathematical methods for analyzing shape and texture in weather satellite imagery to improve forecasts and public safety. Working closely with scientists at the Cooperative Institute for Research in the Atmosphere (CIRA), I focus on two severe weather applications: detecting convective cloud regions in high-resolution visible imagery and characterizing tropical cyclone convective structure and eye formation in synthetic passive microwave imagery. I am member of the NSF AI2ES institute and my work is partially supported by NSF CAIG.
Mitchell, N., Ver Hoef, L., Ebert-Uphoff, I., Moen, K., Hilburn, K., Lee, Y., King, E.J. (2025). Knowledge-Guided Machine Learning: Illustrating the use of Explainable Boosting Machines to Identify Overshooting Tops in Satellite Imagery. Artificial Intelligence for the Earth Systems, 5
Howard, K., Rocheleau, C., Overton, T., Barazza Nava, J., Faldet, M., Moen, K., Soller, S., Stephens, T., Van de Lagemaat, Wijesinghe, N., Wong Dollo, K., Barbosa da Rosa, N., Mueller, J. (2025). A comparison of techniques to improve pulmonary EIT image resolution using a database of simulated EIT images. Journal of Computational and Applied Mathematics, 460, 1-22.
November 9, 2025: Poster presentation, Texture Analysis of Satellite Imagery for Weather Forecasting, CSU Graduate Student Showcase, Fort Collins, CO.
October 21, 2025: Invited talk, Texture Analysis of Satellite Imagery for Weather Forecasting, CSU-Pueblo Math Department Colloquium, Pueblo, CO. Also gave presentation to the math club about graduate school.
July 29, 2025: Poster presentation, Texture Analysis of Satellite Imagery for Weather Forecasting, Third Joint SIAM/CAIMS Annual Meetings (AN25), Montreal, Quebec.
(To be updated)
"Resilient water management modeling" for IHI Corporation with the G-RIPS Japan program (Summer 2024)