Trained in the French school of Data Analysis in Montpellier, Susan Holmes has been working in non parametric multivariate statistics applied to Biology since 1985. She has taught at MIT, Harvard and was an Associate Professor of Biometry at Cornell before moving to Stanford in 1998. She created the Thinking Matters class: Breaking Codes and Finding patterns and likes working on big messy data sets, mostly from the areas of Immunology, Cancer Biology and Microbial Ecology. Her theoretical interests include applied probability, MCMC (Monte Carlo Markov chains), Graph Limit Theory, Differential Geometry and the topology of the space of Phylogenetic Trees. She wrote the book
Modern Statistics for Modern Biology with Wolfgang Huber from EMBL and teaches the material as a crash course (BIOS221) regularly every year. Her current focus is improving the statistical analyses and reproducibility of data in perturbation studies of the Human Microbiome.
Professor Holmes’ main areas of interest are computer intensive methods in data mining and multivariate statistics, especially the bootstrap.