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Faculty Spotlight: Beckett Sterner

The Center is excited to welcome a new faculty member this fall. Dr. Beckett Sterner joins Arizona State University and the Center for Biology and Society from the University of Michigan.

Sterner has made a career of working back and forth between science and science studies, especially history and philosophy of science. He started working in a computational biology lab in college at MIT studying protein function, and then switched to doing history and philosophy of science for his PhD at the University of Chicago in the committee on Conceptual and Historical Studies of Science. He graduated in 2012 and spent two years as an NSF postdoc at the Field Museum in Chicago, working with paleontologist Scott Lidgard. Starting in 2014, Sterner started a second postdoc in the Society of Fellows at the University of Michigan, hosted by the philosophy department there. He arrived at ASU this fall as an Assistant Professor in the Biology and Society program and an affiliated faculty member with the philosophy program. Robert Sokal and Peter Sneath's influential textbook Principles of Numerical Taxonomy in 1963

His research addresses the general 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 threatens to outrun 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 across biology on what sort of theory we should expect to emerge from using these models.  

Gene networks represent genes and their regulatory interactions

Sterner investigates these issues by studying the process and outcomes of mathematization in science: the consequences of making math indispensable for scientific research. Some of his new and ongoing projects include: the impact of computational workflows on the methodology and social structure of systematic biology; big data and design principles for managing pitfalls in data aggregation; integrating model selection and hypothesis testing in paleobiology; and incorporating explicit landscape geometry into our theory of population lineages.