I'm currently working on high-dimensional inference theory and methodology, particularly sparse principal components analysis, with Jing Lei. I also enjoy teaching, from short Stat Bytes lectures to full courses; and I try to make good use of the Eberly teaching center resources here. At home, my wife and I spend most of our time attempting to train a semisupervised deep neural network---that is, raise our baby boy.
Formerly I was a mathematical statistician with the U.S. Census Bureau, working primarily in small area estimation, Bayesian modeling, and data visualization. I've also applied my statistics skillset in transportation engineering, neuroscience, and humanitarian and volunteer work (for DataKind, StatAid, and Statistics Without Borders). I'm a proud graduate of the inaugural class of Olin College, and later of Portland State University's Statistics program.
I'm currently involved with the Statistical Machine Learning Reading Group (SMLRG):
At CMU I have also worked with the Models of Infectious Disease Agent Study (MIDAS) group:
and the CMU-Neurostats group:
Before CMU, I worked at the US Census Bureau in the research directorate:
and before that, in the Intelligent Transportation Systems Lab at Portland State University: