Alex White’s areas of scholarly expertise include statistical modeling in biogeography, quantitative ecology, ornithology, and community phylogenetics. Dr. White’s research focuses on how ecological and evolutionary forces (e.g., dispersal, range expansion, competition, and speciation) interact to mediate broad scale patterns of biodiversity and how those interactions are influenced by local ecological dynamics. This work combines traditional methods in ecology and evolution with modern advances in statistics and computation, particularly those in machine learning and data science. As a Biodiversity Research Data Scientist in the Smithsonian Data Science Lab, he leads projects that leverage digitized museum collections as well as applications of computer hardware technology in edge uses of machine learning for field studies of animal and plant ecology.