Postdoctoral researcher at the Nebraska Evaluation and Research (NEAR) Center and adjunct faculty in Educational Psychology at the University of Nebraska–Lincoln. I work on measurement, missing data, and privacy-preserving synthetic data, and I build R and Shiny tools for the unglamorous middle of applied research: documenting, cleaning, linking, and reporting on administrative data.
Most of it starts the same way — a dataset somebody needs to trust and can't yet.
- recode-studio — clean messy string variables without writing R by hand. Exports the recode rules, so next quarter's data gets the same treatment as last quarter's.
- table-explorer — point it at files or a database and get auto-detected primary and foreign keys, an interactive ERD, and a report you can hand to someone. R/Shiny, with a Python/Streamlit port.
- lspc-weather — skydiving weather for my drop zone. Every flag cites the published USPA, FAA, or club rule behind it, and where nothing published sets a threshold, it raises no flag at all.
- pleasantry — randomized compliments and farewells, from sincere through backhanded to pseudo-Shakespearean. Written in a posit::conf(2026) workshop. Not serious; tested anyway.
Teaching data management and survey methods to graduate students. Generating synthetic versions of Nebraska's statewide longitudinal data so researchers can work with it without exposing anyone. An earlier life in sport and exercise science, which is where the neuromuscular physiology papers came from.