Summary
David Gerard is an associate professor of Statistics with a decade of experience developing hierarchical and multivariate methods for biological data, currently leading research at American University. His work bridges empirical Bayes modeling and computational statistics, with a recent focus on the challenging genetics of polyploid organisms. He has a strong track record from PhD research through a University of Chicago postdoc, mentoring students and building reproducible analysis pipelines for large-scale gene expression and array-variate datasets. David pairs deep theoretical training (PhD UW, MS/BS Ohio State) with hands-on method implementation and teaching, and often tackles problems where nontrivial computation meets complex biological structure.
10 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Statistics, 3.82, Doctor of Philosophy (Ph.D.), Statistics, 3.82 at University of Washington
Master’s Degree, Statistics, 3.94, Master’s Degree, Statistics, 3.94 at The Ohio State University