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Resilience and Data Science for Networked Infrastructures

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If you have a question about this talk, please contact Hector Basevi.

Host: Prof Andrew Howes

Abstract: We live in a time of increased uncertainty and there is a need to monitor our infrastructures and design more resilient systems. Many of our critical infrastructures and ecosystems have a networked dimension. Whilst the resilience and data sampling process is well understood for single dynamical entities or stationary graphs, it is not understood for large-scale networked dynamical systems. This is particularly the case when the size of the network is large (e.g. millions of nodes at the national scale). This talk will present recent advances in understanding the resilience of dynamical networks and optimal sampling theory for data collection on them. This will inform the UK in establishing both a complexity twin and a digital twin for its critical systems.

Biography: Dr. Weisi Guo is an associate professor at the University of Warwick and Turing Fellow. He graduated MEng, MA, and PhD (Computer Science) from the University of Cambridge. He has over 13 years of experience in academia and industry, specialising in network science, signal processing, and telecommunications. He currently leads the Data-Embedded-Networks Lab, with 5 post-docs and 9 PhD students and is PI on £1.7m of funding. He has been twice a runner up of the Bells Labs Prize and a recipient of the IET Innovation Award.

Website: https://warwick.ac.uk/fac/sci/eng/staff/wg/

This talk is part of the Artificial Intelligence and Natural Computation seminars series.

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