Research Expertise and Interest

machine learning, variational inference, Bayesian methods, robustness quantification, applied statistics

Research Description

Ryan is currently an assistant professor of statistics. He earned a PhD in statistics from UC Berkeley, an MSc with distinction in econometrics an  mathematical economics from the London School of Economics, and undergraduate degrees in mathematics and engineering mechanics from the University of Illinois in Urbana-Champaign. Ryan has worked as a postdoctoral researcher at MIT, as an engineer for Google and HP, and served for two years as an education volunteer in the US Peace Corps in Kazakhstan.