I began geophysics research as an undergraduate, focusing on seismology and geodesy, (mostly around Yellowstone National Park). This quickly piqued my interest in volcanic systems and natural disaster preparation and response. Soon after graduating, I volunteered with the geodetic volcanology research team at the USGS Hawaiian Volcano Observatory. I got involved with a lot of volcanic research, fieldwork, and helped install/maintain instrumentation. In doing so, I was introduced to the many advantages and ingenuity of remote sensing techniques like InSAR theory.
My current research focuses on using remote sensing techniques to monitor, detect, and analyze surface deformation caused by natural hazard events, namely volcanoes, landslides, glaciers, and earthquakes. I generate high-resolution Digital Elevation Models (DEMs) and Differential Interferometric Synthetic Aperture Radar (DInSAR) time-series products over both short and long periods of time to investigate changes in topography. I'm interested in applying machine learning to various geophysical data sets to better characterize geophysical phenomena- how these processes are initiated, how they evolve, and the impact they have (or the potential impact they could have) on surrounding environments.