Complex Systems Scientist
Associate Professor of Applied Physics at Dept. of Physics of University of Padua
Head of CoMuNe Lab, Research Group for Multilayer Modeling and Analysis of Complex Systems
Director of the Padua Center for Network Medicine
Director of the Mediterranean School of Complex Networks
National Coordinator of the Italian Chapter of the Complex Systems Society
Scientific Board of the Padua Neuroscience Center
Steering Committee of the Network Medicine Alliance
Topic Leader for the CLAIRE (Confederation of Laboratories for Artificial Intelligence) Covid-19 Initiative
Member of the Complex Systems Society, the Network Science Society and SIFS (Italian Society for Statistical Physics)
Member of MIDAS (Models of Infectious Disease Agent Study), NfoLD (NASA's Network for Life Detection)
I am a physicist studying integrated real-world Complex Systems (biological, socio-technical, communication and economic networks) and their complex dynamics, to understand how multiplexity and interdependencies lead to emergent collective phenomena and resilience to perturbations (see Bio for details).
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Theoretical advance on the representation of complex networks for modeling empirical complex systems, identifying central/influential units and determine the underlying meso-scale organization.
Single and coupled dynamics on multilayer networks for modeling information/awareness propagation, complex contagion, epidemics spreading, consensus mechanisms. Our goal is to better understand robustness, resilience and emergence of collective phenomena in complex networked systems.
Information theory is intimately realted to statistical physics, playing a key role in data science and a variety of applications. We develop theoretical and analytical tools to quantify how complex networks produce and process information, to reduce their dimensionality.
Network geometry is rapidly gaining attention for providing a suitable framework for the analysis of interacting systems. We focus on the application of network diffusion maps to better understand the dynamics of spreading processes and to provide coarse-grained representation of networkd systems.