I am a Project Scientist in the Energy Geosciences Division. My research involves applying machine learning and process-based approaches to model energy and watershed systems. Specifically, I am developing machine learning approaches for modeling snowpack, identifying anomalies in time-series data, and spatial downscaling of future climate projections. Additionally, I am developing physics-based and machine learning approaches for modeling fault reactivation processes during geological fluid injections. I also have a background in computational modeling of soil mechanics at discrete and continuum scales, with emphasis on soil liquefaction.