
Network Science
The Network Science group seek to discover and inspire fundamentally new ways to measure, model, predict, and visualize meaningful interactions and interconnectivity of social, physical, and technological systems. Members in this group are a part of the interdisciplinary Network Science Institute.
Members
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Professor Barabási’s research focuses on biological networks, science of success, applications of control theory to networks, and the development of network models of resiliency in systems.
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Professor Krioukov’s expertise is in latent network geometry, maximum-entropy random graph ensembles and random geometric graphs, causal sets, navigation in networks, and fundamentals of network dynamics.
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Professor Moro’s expertise is in big data, network science, and computational social science, with a focus on human dynamics, collective intelligence, social networks, and urban mobility in areas such as viral marketing, natural disaster management, and economic segregation in cities.
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Research in Professor Santillana’s group focuses on modeling of geographic patterns of population growth, modeling fluid flow to inform coastal floods simulations and atmospheric global pollution transport models, design and implementation of disease outbreak prediction platforms, and mathematical solutions to healthcare.
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Professor Vespignani expertise includes contagion models and adaptive behavior, epidemics in structured populations, resilience of coevolving and interdependent networks, conversations in online social networks, global epidemic and mobility model, and mapping world languages through microblogging platforms.