He obtained his Ph.D. in Statistics and Operations Research from the University of North Carolina at Chapel Hill in 2015. His research focuses on the development, analysis, and application of computational methods for complex network data. Much of his work relies on applying statistical principles from random graph theory to enable inference on various families of networks, including multilayer, dynamic, and weighted networks. James works on networks applications in a variety of areas, including functional brain imaging, political voting trends, and labor market competition. Website for Dr. Wilson.