Modeling how HIV and tuberculosis behave — cell by cell, patient by patient.

My work sits at the intersection of infectious disease biology, quantitative modeling, and data engineering. During my PhD and postdoc at Purdue's Weldon School of Biomedical Engineering, I built cellular-scale agent-based models of Mycobacterium tuberculosis, HIV, and their coinfection — calibrated against in vitro data from the Schlesinger lab (Texas Biomed) and pediatric immune activation datasets from the Indiana School of Medicine.

At Astellas Pharma, I brought my knowledge of stochasticity to industry — using stochastic differential equations, instead of the traditional ordinary differential equations with random parameter distributions, on physiologically-based pharmacokinetic (PBPK) models to generate virtual patient populations that capture real-world patient variability.

Mechanistic modeling of virtual cells by hand is my main passion and using AI for practical analysis tooling to produce the scripts and graphs that make results readable and reusable helps me make the most of my time.