I am a Ph.D. candidate in applied statistics and research methods at the University of Northern Colorado, expecting to graduate in Summer 2026.
My work focuses on causal inference, panel data, and reproducible statistical computing for energy and environmental policy. I am especially interested in policy evaluation settings where the treatment must be constructed from administrative or operational data, identification depends on aggregate instruments or panel designs, and uncertainty has to be assessed through design-based diagnostics and simulation.
Renewable Energy Policy and Power-Sector Emissions Analysis
This project studies causal inference for renewable-policy emissions evaluation using a consumption-side wind-and-solar retail electricity exposure measure, aggregate-instrument estimators, exposure-weight diagnostics, and calibrated simulation checks.
Public code and data: energy-policy-emissions-code
- Causal inference, instrumental variables, synthetic controls, panel data, and time-series analysis
- Simulation-based operating-characteristics analysis and reproducible research pipelines
- Python, R, SQL, SPSS, and SAS
- Graduate research consulting, statistical programming, and applied-methods support