Scott C. Schmidler

This paper introduces a Bayesian variable selection method for identifying selection in phylogenetic datasets, showing it outperforms Dirichlet-process models and avoids phantom selection artifacts.

This paper introduces a Bayesian non-parametric model to analyze microbial growth data, accounting for random effects and improving accuracy in estimating biological effects.