I am a PhD candidate in the Department of Statistics at the University of California, Irvine, being advised by Padhraic Smyth. I am also an organizer and instructor for the UCI Data Science Initiative. My research interests include machine learning, applied statistics, and Bayesian statistics with an emphasis on applications to various forms of human behavior. I graduated Summa Cum Laude with a Bachelor of Science in Mathematics and minors in Statistics and Computer Science from South Dakota State University in 2014, and received a Master of Science in Statistics from UCI in 2016. Before coming to UCI, I worked as an analyst at Wells Fargo, modeling customer churn in retirement accounts. I received Honorable Mention in the 2016 NSF Graduate Research Fellowships Program (GRFP) for work on individual-level mixture models for event data. I am currently an Honorary Fellow in the Machine Learning and Physical Sciences Program (MAPS), a project focused on interdisciplinary team science funded by the NSF Research Traineeship (NRT) program.
Chris Galbraith and Padhraic Smyth. Analyzing user-event data using score-based likelihood ratios with marked point processes. Digital Investigation, Volume 22, Supplement, 2017, Pages S106-S114, ISSN 1742-2876.
uci data science initiative workshops
Introduction to Data Analysis with R
uci coursesSTATS 7 - Teacher's Assistant for introductory course in basic statistics (Winter 2017)