Menglin Liu

I am a Ph.D. Candidate (ABD) in Political Science at the University of California, Davis, with research interests spanning American politics, urban governance, and methodology. My work examines the impact of local political institutions, such as direct democracy and district-based elections, on public policy and governance outcomes.

Methodologically, I specialize in data mining, text analysis, and leveraging large language models (LLMs) to analyze unstructured data. I am the developer of the open-source Python package PoliPrompt, which automates prompt optimization. My ongoing projects include adapting visual language models (VLMs) for political content analysis and improving ordinal classification methods for scaling political concepts.

Beyond academia, I have experience as a Data Analyst for the Committee of 100, where I visualized legislative impacts on land use policies. My interdisciplinary expertise bridges computational advancements with pressing questions in governance, public opinion, and democratic accountability.