William Rand

William Rand examines the use of computational modeling techniques, like agent-based modeling, geographic information systems, social network analysis, and machine learning, to help understand and analyze complex systems, like the diffusion of innovation, organizational learning, and economic markets. He received his doctorate in Computer Science from the University of Michigan in 2005 where he worked on the application of evolutionary computation techniques to dynamic environments. While finishing his doctorate he was involved in a large scale research project that developed an agent-based model of residential land use in the Southeast Michigan area. Later as a postdoctoral research fellow at Northwestern University in the Northwestern Institute on Complex Systems (NICO), he continued to develop his interest in agent-based modeling and evolutionary computation, and began combining these techniques with social network analysis. He is currently co-authoring a textbook on agent-based modeling. Over the course of his research experience, he has used computer models to help understand a large variety of complex systems, such as the evolution of cooperation, suburban sprawl, traffic patterns, financial systems, land-use and land-change in urban systems, and many other phenomena.