Welcome!
I'm an Assistant Professor of Economics at Wake Forest University. I joined Wake after receiving my PhD from Carnegie Mellon in 2022.
I study macro-labor topics related to technological change and inequality. My research uses micro-data to examine how structural features of labor markets -- such as tasks and occupations -- inform macroeconomic relationships, like automation's effects on wages and employment.
My most recent work is on the development of methodology/resources for measuring labor's exposure to technological innovation. I finetune a "small" language model (Sentence-BERT) and use it to (1) match USPTO patent applications with ONET occupational task statements, and (2) perform just-in-time classification of patents and tasks. This allows exposure measures to be quickly estimated for user-defined technologies and task categories, and at a fine cross-sectional and temporal level. Some examples:
The working paper (available here) shows that with training, Sentence-BERT is able to achieve near-GPT levels of matching/classification accuracy -- all while being simpler to use than older NLP methods, free and open-source, and capable of running on a laptop. This substantially lowers the barriers to working with large, textual datasets.
The public dataset and resources should be available in January 2026 -- please check back!