I am a Ph.D. candidate in Political Science at The Ohio State University, with a focus on political methodology and foreign policy decision-making. In my dissertation, I derive a new model, Bayesian Word Embeddings with Automatic Relevance Determination priors, which allows users to measure the meaning of individual words, and incorporates an estimate of uncertainty in the embeddings. I also develop an inference strategy to identify embeddings, so they can be used in regression models for hypothesis testing. I use this model to investigate the determinants of threat perception during the Cold War among elites, drawing on the recently digitized Foreign Relations of the United States. I’ve written a few tutorials, one for R users who want to use the Unity cluster at Ohio State, and another for R users who want an introduction to word2vec in Gensim. My CV is available here, and my resume is available here.
Lately, I’ve been giving the following talk: Identification and Inference in Bayesian Word Embeddings
Ph.D. in Political Science, 2019
The Ohio State University
B.A. in Political Science, 2013
I was the instructor of record for POL4782: Data Analysis in Political Science II in Spring 2018, the syllabus is available here. I taught students regression modeling using ordinary least squares (OLS), and generalized linear models (GLMs) using Maximum Likelihood Estimation. The Rmarkdown template I had my students use for problem sets and materials for getting acquainted with Rmarkdown are available here. I hope you find them helpful!
I was the graduate teaching assistant for the first course in the graduate quantitative methods sequence in Fall 2018. I was responsible holding recitations for teaching students the R software package, the materials I used are available here.