Amy Willis 

Associate Professor 

Department of Biostatistics 
Office #315, Hans Rosling Center for Population Health 
3980 15th Avenue NE, Box 351617 
University of Washington, Seattle, WA 98195 
(206) 543 8027

ad[my-last-name](at)uw(dot)edu

I am a Associate Professor (with tenure) in the Department of Biostatistics at UW. I develop statistical methods for the analysis of ecological data obtained from high throughput sequencing, with a particular emphasis on microbiome data. Microbial communities are incredibly diverse, responsive, and critical to ecosystem function, and new microbiome data is being generated every day by researchers in biology, ecology, medicine, environmental health, agriculture, and many other fields. I develop rigorously grounded statistical and data-scientific tools for the analysis microbiome data that apply across multiple scientific disciplines. I actively develop and maintain my code on github, and engage with my users on Twitter.

From a statistical standpoint, I love quirky and non-standard statistical problems. Non-Euclidean metric spaces, boundary value problems, heavy-tailed estimators, and other situations that fall outside common regularity conditions fascinate me. Microbiome data is high-resolution, high-dimensional, contains hierarchies of information, and suffers from differential data quality, detectability, and missingness -- that's why it's so fun to work with!

The last time I updated this (November 2024), I was interested in assumption-light estimation of differential abundance (and prevalence), accurately estimating phylogenies (at both gene and genome scales), integrating multiple sources of data (e.g., both metagenomic and metatranscriptomic sequencing), predicting the detectability of unculturable organisms, integrating measurement error into models for sequencing data, and outreach aimed at improving the statistical literacy of microbial ecologists. 

CV