I am currently a Research Scientist working in the Modeling and Data Assimilation Division of NOAA's Physical Sciences Lab in Boulder, Colorado. I am interested in advancing coupled data assimilation techniques for the next generation of weather forecasting systems. My main focus is in developing Machine Learning methods that can enable strongly coupled data assimilation, so that observations of the atmosphere can impact estimates of the ocean state, and vice versa, directly within the data assimilation framework.
Before joining PSL, I obtained my Ph.D. in Computational Science, Engineering, and Mathematics from the Oden Institute at UT Austin. My graduate work focused on quantifying uncertainties that are inherent to ocean models, and I implemented a generic, adjoint-based framework to propagate these uncertainties onto predictions from the MIT general circulation model. I used this framework to show how sparse observations of the ocean state reduce uncertainty in simulation-based estimates of ocean driven melting underneath the Pine Island ice shelf, which is fed by one of the fastest flowing glaciers in Antarctica. The results showed how valuable observations in this region are for constraining modeled quantities.
When I'm not working, I love to go rock climbing, skiing/snowboarding, trail running, and cycling in the beautiful Colorado outdoors.