Hi! I am an applied statistician with research interests in Gaussian process surrogate modeling, spatial and spatiotemporal statistics, and statistical learning with applications to the environment and ecology.
In the past, I worked on modeling the spatial relationships between big sagebrush and perennial grasses in the Great Basin to gain insight into the process of shrub-grass facilitation. I examined whether spatial relationships between shrubs and grasses changed over precipitation and grazing gradients. I also worked on a project in which I compared various statistical learning and spatial models for predicting stream temperatures over stream networks. My PhD dissertation focused on developing novel statistical/computational workflows for bias-correcting output from numerical climate models. My recent research involves the development of a Gaussian process surrogate modeling approach for forecasting stream temperature profiles up to 30 days in the future. I am currently a postdoctoral appointee in data science at Sandia National Lab. |