Welcome!
Data analysis and visualization are cornerstones of quantitative political science research. On this site, you’ll find a veritable portfolio of my various projects and analyses, as well as details about the nuts and bolts of my research and techniques used to analyze original datasets and create professional looking visualizations.
My interests encompass a wide variety of subfields and research questions, and my toolbox of methods is always expanding. Whether I’m applying Monte Carlo methods to measure the uncertainty of US foreign aid’s effect on bilateral migrant inflows into the US:
Or applying versatile tools such as dwplot() in R’s dotwhisker package to display results from OLS and Tobit estimation of gravity-type equations of the impact of numerous covariates on bilateral immigration using dyadic panel data:
Or making use of unsupervised methods of machine learning for text analysis to identify latent topic structures and topical prevalence in primary and general election presidential debates:
I’ve used each research project as an opportunity to expand my skills.
Though my passion for quantitative methods was initially kindled my first semester as a graduate student in political science, much of what I’ve learned is self-taught. My desire to continually imporve and learn has proved a valuable asset that has always pushed me to greater heights. Hopefully this site (while a work in progress) will adequately display my persistent drive for improvement and exploration.
Recent Articles
Making Better Graphics for Structural Topic Model Objects with R
How to Model the Gravitational Pull of Bilateral Foreign Aid on Bilateral Immigration
Machine Learning for Text Analysis with R