The course focusses on the relation between network structure and the time evolution of typical dynamical processes on them. After having consolidated the nomenclature and fundamental mathematical concepts (mainly from linear algebra and non-linear systems stability), the course will highlight key differences between fully mixed systems and network systems when considering the same processes. Dynamical systems of interest are continuous time consensus and spreading mechanisms typical of virus spreading in epidemiology, but also used beyond that. The course focusses on analytical properties of network and touches upon numerical and experimental results available from the literature

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Guest Lecture: Giuliano Punzo University of Sheffield Current Position School of Electrical and Electronic Engineering, The University of Sheffield This role includes both research and teaching beside administrative duties. Currently my team is composed of 3 PhD student, 1 Research Associate and 1 Research Software Engineer. Other University roles: - Director and Transport Lead for the Urban Flow Observatory, - Head of Sustainability for the School of EEE - University Transport Study Group correspondent for Sheffield. - Chair of the University Transport Advisory Group. Other academic roles: STFC DAFNI Strategy board member. Fellow of the Higher Education Academy Research Areas Within a common theme of socio-technical systems, specific research areas include: • Sustainability and resilience, large infrastructure projects, fragile and conflict environments. • Dynamical system theory, control theory, complex systems dynamics, bio-inspired systems, multi-agent systems, infrastructure, transport. • Network science, consensus and algebraic graph theory. • Game theory Dynamic and differential games on networks, oligopolies and social dilemmas Each lecture will be 2 hour long, including a 15 minute break. Lecture 1. Networks and algebraic graph theory Lecture 2. Elements of dynamical systems and stability Lecture 3. Linear consensus systems (with examples) Lecture 4. Spread and recovery processes in network systems (biological inspired modelling of fault/disruption propagation in systems) Lecture 5. Controllability and Resilience Lecture 6. Applications

In presenza

Sviluppo di project work in team

P.D.2-2 - Maggio