Biology Seminar Series - Austin Ferguson, Grand Valley State University

Evolution is famously a slow process, which can make empirically studying it difficult. Experimental evolution, whole-genome sequencing, massive data collection efforts, and other recent advancements have made great progress, but many questions still lie outside the realm of empirical feasibility. Here we discuss computational evolution, where populations of evolving digital organisms are used to ask carefully designed questions about evolution. We will start with an overview of computational evolution and then pivot to a few recent vignettes. Specifically, we will discuss how computational models have been used to study historical contingency in evolution via replay experiments, and how those results may influence future wet-lab studies. Additionally, we will discuss how such models are being used alongside population genomics to study the evolutionary dynamics of invasive Hemlock Woolly Adelgid as they spread across eastern North America. Overall, we will discuss how computational studies complement traditional evolutionary biology research when appropriate models are being used and appropriate questions are being asked.

Austin Ferguson is an Assistant Professor of Computer Science at Grand Valley State University. His research uses agent-based computational modeling to empirically investigate questions in evolutionary biology theory. Specifically, his recent work has focused on historical contingency in evolution, evolvability, population structure, and how the evolutionary dynamics of invasive species. Before starting at GVSU, he earned a Dual PhD from Michigan State University in Computer Science and Ecology, Evolution, & Behavior.