Guinness studies modeling and computational issues that arise in the analysis of spatial-temporal data, particularly data from the Earth Sciences.
He has made fundamental contributions to spectral methods and advances to Vecchia's Gaussian process approximation. He is the lead developer and maintainer for the GpGp R package, an efficient and user-friendly software package for fitting Gaussian process models. He teaches courses in statistical computation and linear models at various levels. Guinness received his undergraduate degree in mathematics and physics from Washington University in St. Louis in 2007 and his Ph.D. in statistics from the University of Chicago in 2012.
