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Jon M. Kleinberg
Cornell University
The growth of the Web, and the increasingly availability of massive network datasets across the physical, natural, and social sciences, has crystallized a view of large networks as complex phenomena, not just engineered artifacts --- as systems that evolve according to their own principles and exhibit characteristic large-scale structure. Against this backdrop, recent research has employed combinatorial and probabilistic techniques to formulate new models for network growth and structure that capture some of these characteristic properties, and has developed algorithms for analyzing complex networks with applications ranging from Web search to the understanding of large social networks.