My research interests pertain to mathematical applications in ecology. I'm currently working for Dr. Gregory Pasternack at the University of California, Davis. Dr. Pasternack and I have focused on spatial modeling of the riparian canopy on the Lower Yuba River. These data are LiDAR-derived, and are therefore incredibly resolved. This yields data that are autocorrelated. When neglected, spatial autocorrelation violates the independence assumptions of most statistical models, and leads to over-stated degrees of freedom. Dr. Pasternack and I have generated Bayesian models that explicitly address this autocorrelation, which are able to borrow strength from neighboring data. This research, in many ways, builds upon what I learned during my master's program, with Dr. Robert van Woesik. Dr. van Woesik and I addressed spatial patterns among corals in the Florida Keys. We found that the corals were largely homogenized. Prior to that study, I worked with Dr. van Woesik on time-series models of Great Lakes fisheries using wavelets. These studies all consider autocorrelated data. Contemporary computing methods enable new methods of modeling autocorrelated data. In the future, I hope to find ways of explicitly modeling temporally and spatially autocorrelated data structures.