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Competition, Innovation, and Evolution.

Stochastic processes, mathematical biology, evolutionary theory (especially the levels of selection problem), community assembly, co-evolution and the evolution of virulence. My favorite study systems are the microbial jungles of the human microbiome, the investment jungles of human financial markets, and the linguistic jungles of social media.


Some Specific Topics:

Community Assembly & Stochasticity

Neutral Theory, stabilizing mechanisms and how they operate in stochastic environments. 


University of New Mexico

Bachelors degrees in Applied Math & Biology.

Phylogenetic factorization

Most datasets are described using the elementary basis - variables correspond to observations on the tips of the phylogeny.

I recently developed a method that allows researchers to describe their data in terms of variables corresponding to differential abundances along edges of the tree. "Phylofactorization" is a matrix factorization and constrained factor analysis where "factors" are putative functional ecological traits that arose along an edge in the tree. There's an R package on github and a tutorial


Princeton University

Ph.D. in Quantitative and Computational Biology

view thesis here


Duke University

Post-doctoral research


Montana State University

Research Scientist

Pathogen Spillover and Epidemiology

Which pathogens spillover, which non-human reservoirs do they tend to come from, and how can we combine information at multiple scales ranging from reservoir ecology to human behavior for honest assessments of spillover risk?

Once a pathogen spills over, which data sources can help us learn the most about an ongoing epidemic (hospital admissions? outpatient visits? confirmed cases? sewage??)

A pandemic unfolds in a story of thousands of local epidemics - how can we compare these many local epidemics to better understand a global pandemic?


Chief Scientist, Selva Analytics LLC

Mathematical, statistical & epidemiological consulting

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