About Me
I am a PhD candidate in the Remote Sensing Ecohydrology Group at Stanford University. I seek to improve our ability to model the terrestrial water cycle by better representing vegetation variability in hydrologic models. I use physical models, remote sensing data, and machine learning methods to pursue my research goals.
I grew up in Southern California where I developed my love for trail running, climbing, and all things outdoors. I am a graduate of the University of Notre Dame, where I received my B.S. in Environmental Sciences and a minor in Catholic Social Tradition.
Improving land surface model predictions of evapotranspiration and streamflow by better representing vegetation variability
Generating a long-term, deep learning-based dataset of live fuel moisture content from combined microwave and optical remote sensing
Validating the accuracy of vegetation traits retrieved from a combination of process-based and machine learning models