I am currently a full-time researcher and administrator in the Stanford Social Neuroscience Lab.

My research interests span social psychology, political science, and cognitive neuroscience. Broadly, I’m interested in exploring the neural and attitudinal correlates of political partisansip, as well as designing interventions to reduce polarization.

For a primer on my interests, read my Master’s thesis here.

I employ a variety of computational methods to explore these subjects, ranging from conventional linear and logistic regression to more nuanced, Machine Learning approaches (e.g., regularization, clustering, and decomposition).


Measuring Polarization


Among my principal interests is assessing the degree to which political polarization influences our interactions with members of the opposite party. Analyzing the downstream effects of polarization and their covariates has certainly never been more relevant to our understanding of intergroup relations.



By leveraging social psychological theoretical frameworks and contemporary algorithmic approaches (e.g., Natural Language Processing and PCA) together, my aim is to shine a light on the antecedents of polarization in order to structure policy syntax in a minimally polarizing way.


“What the Hell Happened” data obtained via Data For Progress + My Analysis