About me

I am an atmospheric modeler, boundary layer meteorologist, computational hydrologist, engineer, teacher and mentor working to improve global understanding of the connection between the land surface we live on and the atmosphere above us. My research aims to build models for water, carbon and energy that apply in data rich uniform cropland, or poorly instrumented, vast mountain forests, allowing environmental scientists, modelers and decision makers in all parts of our earth to make informed decisions. To this end, I work to harness a wealth of satellite and in-situ data, high resolution models, fundamental physics, and modern machine learning methods to improve predictions of how water, energy, and carbon moves across the land-atmosphere continuum, especially in complex terrain and heterogeneous landscapes.

Instrumental in achieving this goal is educating the next generation of industry leaders and future academic collaborators to instill a passion for our planet, and an in-depth understanding of the nuances of environmental data and modeling. I work to create an environment that promotes both independent and collaborative learning, heavily focused on meaningful challenges, active participation, and project-based learning.

I started my academic career with a B.S. in Civil and Environmental Engineering at U.C Berkeley working in the Dr. Sally Thompson ecohydrology lab, before coming to Duke in 2019 to work on a PhD focused on improving the coupling of the land and atmospheric systems in earth system models with Dr. Nathaniel Chaney funded under the NOAA Coupling of Land and Atmospheric Subgrid Parameterizations (CLASP) team. In August 2024, I began an NSF Postdoctoral Fellowship at the University of Utah to study potential anisotropy based generalization of monin-obukhov similarity theory to imrpove parameterizations of heat, moisture, carbon and momentum exchange with the atmosphere.