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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.

[CV] [.bib]

[Homepage]

[Team] [Students]

[AI & Global Development Lab GitHub]

[Google Scholar] [UT Profile]

[YouTube Tutorials] [Data Assets]

[Effect Heterogeneity with Earth Observation in Randomized Controlled Trials: Exploring the Role of Data, Model, and Evaluation Metric Choice] [.bib]*

[Planetary 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.

ConnorJerzak.com/Research