Ryan Tibshirani


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Short bio

I am an Associate Professor jointly appointed in the Departments of Statistics and Machine Learning at Carnegie Mellon University. I joined the Statistics faculty at Carnegie Mellon University in 2011, and I joined the Machine Learning faculty in 2013. I did my Ph.D. in Statistics at Stanford University in 2011. My thesis advisor was Jonathan Taylor. Before that, I did my B.S. in Mathematics at Stanford University in 2007.

My research interests lie broadly in statistics, machine learning, and optimization. More specifically, my interests include high-dimensional statistics, nonparametric regression, selective inference, distribution-free inference, graph-based learning, convex optimization, numerical methods, and implicit regularization. My main applied focus at this time is on methods for forecasting epidemics (primarily seasonal flu).

I am currently serving as an Associate Editor for: I am also on the Editorial Board for the Springer Series in the Data Sciences. I am also occasionally an Area Chair for the conferences: Artificial Intelligence and Statistics (AISTATS), International Conference on Machine Learning (ICML), and Neural Information Processing Systems (NIPS) (usually just for one of these conferences per year).

A full CV can be found here.