Morgan Kain is a quantitative biologist and statistical modeler with 12 years of experience applying advanced statistical and mathematical tools to problems in ecology, epidemiology, and public health. Trained to PhD level in biology, they are fluent in R (tidyverse, ggplot, shiny), Bayesian modeling in Stan/JAGS, and reproducible workflows with Git/GitHub, renv, and targets. Their work spans GLMMs/GAMMs, compartmental and partially observed epidemiological models, simulation-based power analysis, and uncertainty-aware forecasting and imputation. Morgan has collaborated with researchers, public health departments, and communities across five continents, translating complex analyses into accessible visualizers and public-facing tools (e.g., COVID and dengue-focused applets). Currently combining scientific consulting on vector-borne disease transmission with a mathematical statistician role at USDA APHIS, they bring both rigorous theory and practical, community-oriented communication to study design and infectious-disease inference.
12 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD, Biology, General, 4.0, Doctor of Philosophy - PhD, Biology, General, 4.0 at McMaster University
Bachelor's degree, Ecology and Evolutionary Biology, 3.76, Bachelor's degree, Ecology and Evolutionary Biology, 3.76 at University of Pittsburgh
Master's degree, Biology, General, 4.0, Master's degree, Biology, General, 4.0 at East Carolina University
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Morgan Kain - Scientific Consulting Modeling Vector-borne Disease Transmission