Research Bio
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.
Research Expertise and Interest
machine learning, variational inference, Bayesian methods, robustness quantification, applied statistics
Teaching
Linear Modelling: Theory and Applications [STAT 151A]
Supervised Independent Study and Research [STAT 199]
Individual Study Leading to Higher Degrees [STAT 299]
Modern Statistical Prediction and Machine Learning [STAT 154]
Supervised Independent Study and Research [STAT 199]
Modern Statistical Prediction and Machine Learning [STAT 254]
Directed Study for Graduate Students [STAT 298]
Directed Study for Graduate Students [STAT 298]