Causal inference,
computation,
and global development.
We develop statistical methods and software for causal inference using satellite imagery, text, and large-scale administrative data. Department of Government, University of Texas at Austin.
Causal ML
Remote sensing
Text-as-data
Experimental design
Open-source software
Visualization backbone
Research visuals
A selection of recent visuals. Each tile links to a paper, project, or explainer (often on connorjerzak.com).
Approach
Methods you can audit
Combining causal inference, machine learning, and domain knowledge to produce interpretable estimates with uncertainty, backed by open tools and reproducible workflows.
Causal design
Measurement at scale
Text & organizations
Featured
Selected projects
Selected work across causal ML, remote sensing, text-as-data, and experimental design.
