Nicola Perra, Ph.D.
  • Home
  • About Me
  • Research
    • Dynamical Processes on Time-Varying Networks
    • Contagion Models and Adaptive Behavior
    • Epidemics in Structured Populations
    • Global Epidemic and Mobility Model: GLEaM
    • Modeling and Studying Online Social Networks
    • Resilience of Coevolving and Interdependent Networks
    • Centrality Measures on Complex Networks
  • Publications
  • In the Press
  • Softwares and Online Projects
  • Talks
  • Contacts
  • Collaborators
  • Events
    • TNets14
    • TnetSphys'14
    • ChASM 2014
    • TNets13
    • ChASM 2013
    • ChASM 2012
  • Teaching
  • QuiProCore
  • Home
  • About Me
  • Research
    • Dynamical Processes on Time-Varying Networks
    • Contagion Models and Adaptive Behavior
    • Epidemics in Structured Populations
    • Global Epidemic and Mobility Model: GLEaM
    • Modeling and Studying Online Social Networks
    • Resilience of Coevolving and Interdependent Networks
    • Centrality Measures on Complex Networks
  • Publications
  • In the Press
  • Softwares and Online Projects
  • Talks
  • Contacts
  • Collaborators
  • Events
    • TNets14
    • TnetSphys'14
    • ChASM 2014
    • TNets13
    • ChASM 2013
    • ChASM 2012
  • Teaching
  • QuiProCore

Resilience of Coevolving and Interdependent Networks

Co-evolution is a fundamental component in any formal model of network formation and evolution. This amounts to state that the understanding of how people affect the configuration of their local network while simultaneously being affected by that network is at the core of the network structure and nodal characteristics. Co-evolution as a key dynamical feature is particularly relevant in the understanding of the network response in case of exogenous or endogenous stress condition. We are working on the mathematical understanding of the percolation transition in co-evolving networks in which information and damages induces and adaptation and restructuring of the network. In particular we aim at the classification of the vulnerability properties according to different co-evolution mechanisms and the development of optimization algorithms that find structures with maximum resilience.

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