My research focuses on the question, “When and why is mathematics useful for biology?” Biologists have determined the sequences of billions of nucleotides in thousands of genomes, and they have measured the expression levels of tens of thousands of genes across numerous species. However, their appetite for data is quickly outrunning their ability to give it theoretical significance. The movement to quantify life, exemplified here by genomics and its descendants, is no simple benefit to biology: at minimum, it poses major challenges for the nature and practice of biological theory. One leading solution is the introduction of computer modeling into biological theorizing, but little consensus exists among biologists on how and when computer modeling helps.  

I investigate these issues by studying the process and outcomes of mathematization — i.e. the consequences of making math indispensable for scientific research. Some new and ongoing projects include: the impact of computational workflows on the methodology and social structure of systematic biology (taxonomy/phylogenetics); big data and principles for managing flawed data aggregation; integrating model selection and hypothesis testing in paleobiology; and incorporating explicit landscape geometry into our theory of population lineages.