Biography

I am a PhD student at the University of Washington working on problems in cosmology and astronomical instrumentation, with a focus on using machine learning and forward modeling to extract physical insight from complex data. My current work spans two threads: developing deep-learning–based optical system diagnostics for the Vera C. Rubin Observatory, where I use convolutional networks and domain adaptation to infer telescope aberrations in real time; and building fast, physically informed emulators to model the impact of reionization and baryon–dark matter streaming on the small-scale structure of the universe. I’m broadly interested in methods that connect simulations and observations and finding optimal ways to deal with large volumes of data using machine learning.