Interested in the convergence of Natural Language Processing (NLP), Text Mining, Economics, and Finance.
I develop computational text analysis methods bridging machine learning and economics to extract policy-relevant insights from language at scale. My research treats text as data, applying probabilistic models in R, and natural language processing to uncover how narratives in policy documents and economic communications shape expectations and outcomes. This work sits at an intersection where statistical learning provides the tools, economics provides the questions, and careful empirical design connects the two.