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 sparse estimation, nonparametric estimation, selective inference, changepoint detection, learning on graphs, first-order optimization, and implicit regularization. My main applied focus at this time is on methods for forecasting epidemics (primarily seasonal flu).

I am currently an Associate Editor for the Annals of Statistics and Journal of Machine Learning Research (JMLR), and I am also on the Editorial Board for the Springer Series in the Data Sciences. In the past, I've been an Associate Editor for Biometrika and Statistical Analysis and Data Mining, and an Area Chair for Artificial Intelligence and Statistics (AISTATS), International Conference on Machine Learning (ICML), and Neural Information Processing Systems (NIPS) (I am usually AC for just one of these conferences per year).

A full CV can be found here.