Senior Researcher at the National Renewable Energy Lab with a focus on enhancing physical modeling through integration of physics-based and machine learning methods. Lead developer on large codebases with users from 50+ institutions and 50+ countries. Publications and presentations relating to generative machine learning, renewable resource modeling, and earth system modeling. Proven ability to lead interdisciplinary teams, develop innovative solutions, and communicate complex scientific concepts effectively.
I received a Physics Ph.D. from Cornell University in 2019. My thesis was titled "Analysis of Low-Frequency Climate Variability Through Computational Modeling and Tree-Ring Data Synthesis." My research interests mostly lie at the intersection of climate science and machine learning. This also includes computational fluid dynamics, physics based modeling and computer graphics, flight simulation, and robotics.
I graduated from Georgia Southern University in 2012, where I received a Physics B.S., Magna cum Laude, completed the University Honors Program and participated in a number of research projects. My honors thesis was titled "Prototyping method for Bragg-type atom interferometers." I received an M.S. in Physics from Cornell in 2016. My Masters thesis was titled "VR Quadcopter Telepresence Proposal".