News, April 2021:

🎉 I defended my dissertation, “Understanding Political Communication with Contextualized Methods from Natural Language Processing”! 🎉

I am the first person to successfully defend a PhD dissertation in Data Science at NYU’s Center for Data Science.

About me

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, and transfer learning.

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 working in managing editorial at W. W. Norton. For details about my professional experience, visit my LinkedIn.

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.