About me

I am a political scientist with a love of data and data analysis, which I have successfully translated into a career at the intersection of political economy and computational research. My research explores how domestic and international institutions shape economic performance, using both quantitative methods and text analysis. To tackle these questions, I have developed widely used datasets, software tools, and methodological approaches that enhance empirical research in political science and economics. The work has appeared in political science journals such as International Organization, British Journal of Political Science, Journal of Politics, and International Studies Quarterly, and other journals.

Beyond my own research, I am the author of several software packages for Stata, Python, and R to streamline data analysis and statistical modeling. Most of my work in Stata involves utilities or tools for quantitative analysis. These include dropbox (to locate a user’s Dropbox folder in Stata), ccode (for converting between country coding schemes), and ctyfind (to retrieve country names based on classification systems). Additionally, I co-developed medeff for mediation analysis and poet for sensitivity analysis.

At Columbia’s History Lab, I have moved into natural language processing and text analysis. I wrote a Python pipeline to perform Named Entity Recognition and Named Entity Linking on History Lab’s collection of more than 5 million documents. I also wrote Stata and R interfaces for History Lab’s API which allow users to download our data using either program.

My commitment to advancing data accessibility and computational tools continues to drive my work, bridging the gap between political science, economics, and cutting-edge data science techniques.