I am interested in the patterns of diversity exhibited by ecological communities and the biological processes that shape them. In particular, I use math to study coevolving ecological communities and develop model-based statistical methods to measure coevolution in the wild. I also develop flexible mathematical frameworks for modelling ecological and evolutionary processes.

Current Position & Trajectory

I am a second-year postdoctoral researcher at Michigan State University in The Bradburd Lab. My current research applies mathematical and computational approaches to elucidate the genomic signature of host-parasite coevolution in continuous-space. My long-term goal is to start a lab with two primary objectives. The first is to integrate mathematical approaches to genetics and community ecology to understand the causes and consequences of coevolution across spatial, temporal, and taxonomic scales. The second is the development of novel statistical methods to quantify coevolutionary processes.

PhD Work

I defended my PhD June 30, 2020. My dissertation contributes to a coevolutionary theory of community ecology with a focus on plant-pollinator networks. Using Diffusion Limits of Measure-Valued Branching Processes (e.g., super-Brownian motion), I introduced an approach to derive the stochastic dynamics of populations and quantitative traits from biological first principles (Week et. al. 2021). Using this framework, I have investigated the evolutionary dissolution of mutualisms experiencing coevolutionary arms races (Week & Nuismer 2021) and have developed a Maximum Likelihood method to infer the strength of coevolution between pairs of species using spatially structured phenotypic data (Week & Nuismer 2019). My defense was recorded and can be viewed here. Interactive slides are available here.