I am currently a forth year PhD student in the Department of Statistics at the University of Washington, working under the supervision of Dr. Tyler McCormick. I was a research intern at Microsoft Research during summer 2016.
I am broadly interested in statistical, mostly Bayesian, methods for large and noisy social science and demography data. In particular, my current research focuses mainly on characterizing dependency structures using Bayesian graphical models while accounting for different types of informative prior information.
Probabilistic Cause-of-death Assignment using Verbal Autopsy A Bayesian framework to flexibly quantify the uncertainties in the noisy data from multiple sources in verbal autopsy analysis. Joint work with Tyler McCormick (UW), Sam Clark (OSU), Clara Calvert (LSHTM), and colleagues at HDSS sites.
openVA: A Comprehensive R package for VA Analysis openVA provides a wrapper class for a suite of VA packages: InSilicoVA, InterVA4, Tariff and upcoming NBC package. It implements all the major VA algorithms currently been used, and provides simple syntax to analyze, report, and visualize VA data. Joint work with Tyler McCormick (UW) and Sam Clark (OSU).
Sparse Motifs: Discovering Structure in Massive Graphs A parsimonious model that captures local structure in large-scale telephone networks through motif statistics. By utilizing a Bayesian factorization algorithm, we could characterize dependence structure in these network statistics and learn the adoption process of network goods. Joint work with Tyler McCormick (UW) and Joshua Blumenstock (Berkeley).