I'm a master's student in Statistics (University of Central Florida, expected December 2026) working toward a career in biostatistics. My thesis develops Bayesian and frequentist uncertainty-quantification methods for Positronium Lifetime Imaging, an emerging extension of PET imaging, advised by Prof. Hsin-Hsiung Huang.

I like problems that sit between rigorous statistical methodology and real applied questions — from medical imaging to environmental policy.

• Languages: Python, R, SQL
• Methods: Bayesian Inference & MCMC, Regression (linear, logistic, beta, ridge, lasso), GLM, Design of Experiments, Machine Learning
• Tools: PyTorch, statsmodels, scikit-learn, spatial data (sf, terra), LaTeX, Tableau

• fl-conservation-regression — Beta regression on what drives land conservation across Florida's 67 counties, built end-to-end from raw spatial data (FGDL, NLCD, Census) to a written executive summary.
• pli-lifetime-estimation — Maximum-likelihood and conjugate Bayesian estimators for positronium decay rates; an early "toy example" of some of my thesis methodology (to be published post-defense this fall)
• paper-helicopter-doe — A hands-on design-of-experiments study (factorial and response-surface designs) optimizing paper-helicopter flight time from data I collected.
• statistical-ml-implementations — ML methods built from the math up: CNNs, SVDD with directional-data kernels, an autoencoder for anomaly detection, and transformers.

• 📫 katrina.a.stephenson@gmail.com
• 🎓 Member, American Statistical Association