(jacksongorham at gmail dot com)
I completed my Ph.D. in statistics in June 2017 at Stanford, advised by Lester Mackey and Emmanuel Candes. Earlier, I received my B.S. (with honors) in mathematics from Stanford University in 2006 and my undergraduate advisor was Matthew Kahle. My doctoral dissertation was the 2017 winner of the Savage award in theory and methods.
My interests are in scalable machine learning, convex optimization, Stein's method, and data visualization. I've interned at Counsyl, worked as a data scientist at Facebook, and currently am a data scientist at Opendoor. I do not think there's a best programming language, and I'm neither a frequentist nor a Bayesian. My preference is for whatever works best!