Bio | Papers {Substantive, Methodological} | Visualizations
Present:
[1.] Assistant Professor in the Department of Government at the University of Texas at Austin.
[2.] Consultant, Institute for Health Metrics & Evaluation (IHME), University of Washington.
Past:
[1.] Visiting Assistant Professor in the Department of Government at Harvard University (2024).
[2.] Postdoc, AI & Global Development Lab (2021-2022).
Methodological research: AI and global development, earth observation data for causal inference, adversarial dynamics, computational text analysis.
Substantive research: Political economy, social movements, descriptive representation.
[AI & Global Development Lab GitHub]
[YouTube Tutorials] [Data Assets]
[Effect Heterogeneity with Earth Observation in Randomized Controlled Trials: Exploring the Role of Data, Model, and Evaluation Metric Choice] [.bib]*
[A Scoping Review of Earth Observation and Machine Learning for Causal Inference: Implications for the Geography of Poverty] [.bib] [Data]*
[Image De-confounding] [.bib] [Code]
[Can Large Language Models (or Humans) Disentangle Text Features?] [.bib] [Code]*
[Image-based Treatment Effect Heterogeneity] [.bib] [Code]
[Non-parametric Content Analysis] [.bib] [Code]
[Linking Datasets on Organizations Using Half A Billion Open Collaborated Records] [.bib] [Code]
[Degrees of Randomness in Rerandomization Procedures] [.bib] [Code]
[Where Minorities are the Majority: Electoral Rules and Ethnic Representation] [.bib]
[The Composition of Descriptive Representation] [.bib] [Code]
[Housing Values and Partisanship: Evidence from E-ZPass] [.bib]
*indicates joint work with graduate student co-author(s). See [Students] for more information.
