I am a Research Scientist in the D-Lab at UC Berkeley. My research focuses on the societal impacts of machine learning models, with an emphasis on understanding the norms and values elicited from large language models. I also lead and support a range of social science projects, spanning hate speech detection, education, and computational humanities.
I previously obtained my PhD in the Physics Department at UC Berkeley, conducting research in the Redwood Center for Theoretical Neuroscience under Kristofer Bouchard and Mike DeWeese. My graduate research focused on neural variability: its structure, implications for neural coding, and impacts on phenomenological models of neural activity. My graduate work was funded by the Department of Defense through the NDSEG Fellowship.
I obtained my undergraduate degree in Physics and Computer Science at Washington University in St. Louis, where I studied the stability of hybrid stars under Mark Alford.
I’ve also worked at the intersection of data science and public interest, applying machine learning in mission-driven contexts. I’ve completed a DataCorps project with DataKind, a Data Fellowship with Delta Analytics, and a Data Science for Social Good Fellowship at the University of Washington.