Research
My research lies at the intersection of survey sampling, missing data analysis, and statistical learning. I develop rigorous inference methods with a focus on calibration weighting, entropy-based estimation, and high-dimensional settings.
Research Areas
Survey Sampling
Calibration weighting, model-assisted estimation, generalized entropy methods
Missing Data Analysis
Fractional imputation, propensity score methods, non-probability samples
Machine Learning
High-dimensional variable selection, ensemble methods, transfer learning
Software
GECal — An R package for Generalized Entropy Calibration in survey sampling. Available on CRAN.
calibration — An R package providing an integrated workflow for survey-weight calibration with a modern API, structured solver diagnostics, and extensible solver backends.