I am a PhD candidate in Data Science at NYU’s Center for Data Science. I develop NLP tools for understanding texts, with an emphasis on applications in political communication. My research interests include representation learning, estimation methods for text, transfer learning, and clustering methods.

My dissertation is entitled “Contextual NLP tools for understanding political communication” (coming soon: spring 2021).

About me

My background is in political science, with a focus on quantitative methods and text analysis. I earned a BA, summa cum laude, in English literature and political science from Columbia University (2011). I also hold a MA in political science from NYU (2018) and a MPhil in data science from NYU (2020).

I have worked as a research intern in the AI group at Bloomberg, and as an engineering intern on the Shiny team at RStudio. Before grad school, I worked at a nonprofit and in book publishing.

Where to find me

For details about my professional experience, visit my LinkedIn.

I’m a supporter of open source software and I have a few R packages on CRAN.

If you’re an NYC-area NLPer, you might recognize me from NYU’s NLP and Text-as-Data Speaker Series, which I coordinated from 2017–2020.