I am currently working on a machine learning in astronomy project looking at how computational tools brought from industry and the larger scientific world mesh with astronomy analytic processes. For this project, we are using Hubble data and popular libraries such as Scikit-learn and Tensorflow. More to come here soon (insert this site is under construction gif here)
During my graduate school time at UCLA, I studied astronomy infrastructures of data and code- from large, international governing bodies to small research groups at universities. (resulting in this dissertation). I studied people, places, policies, instruments, and knowledge produced from these efforts. I have done field work and interviewed astronomers across the globe, learning a great deal about what it takes to design, build, and deploy telescopes both on earth and in the sky. I’ve had the pleasure of observing all manners of astronomy activity: from visiting both Subaru and Keck telescopes atop Maunakea, to the dark basement at Harvard where the old glass plates are being scanned into digital FITS files for preservation purposes. I’m interested in the digital history of astronomy, and how this informs software preservation in decades-long scientific projects.