장소: 제1과학관 31214  e+첨단강의실 

초록: As a premier analytical framework for studying complex systems, most complex network studies thus far have been focused on single-layer framework. It becomes increasingly clear, however, that many real-world complex systems are multiplex---nodes interact with multiple types of interactions (network layers) which co-exist, co-evolve, and co-operate. Unraveling the multiplexity and re-assembling in proper context will be crucial in improved understanding the interplay of such multiplex interactions that confer nontrivial consequences on network structure and dynamics. Here we present some recent progress towards understanding the effect of network multiplexity. Topics to be discussed include: the concept of correlated multiplexity, a generalized formalism for percolation in correlated multiplex networks, and its topological robustness and biconnectivity properties, from structural point; a network evolution model based on the coevolution of network layers; effects of multiplexity on the threshold cascade process, epidemic spreading, and opinion dynamics, from network dynamics point.