Computational Epidemiologist & Health Data Scientist 

I am a computational epidemiologist and applied mathematician (PhD, University of Missouri–Kansas City, 2026) working at the intersection of infectious disease modeling, health data science, and One Health. I build mechanistic, statistical, and machine-learning models that turn large-scale clinical and population data into decision-relevant insight on disease transmission, antimicrobial resistance, and healthcare-associated infection.

My work spans peer-reviewed research — including first-author studies in One Health and the Journal of Hospital Infection — and applied modeling with partners including the CDC and urban hospital systems. I work primarily in Python and R, using methods from Bayesian inference and agent-based modeling to data-driven discovery of dynamical systems (SINDy) and predictive machine learning on electronic health records.