Complex Systems Scientist
Associate Professor of Applied Physics at Dept. of Physics of University of Padua
Lead 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
Member of Complex Systems Society, Network Science Society, SIFS (Italian Society for Statistical Physics), MIDAS (Models of Infectious Disease Agent Study), NfoLD (NASA's Network for Life Detection)
QTech (Padua Quantum Tech Center)
Physicist studying integrated real-world Complex Systems (biological, socio-technical and engineering networks) and their complex dynamics, to understand how multiplexity and interdependencies lead to emergent collective phenomena and resilience to perturbations.
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>> Resilience against climate change: we analyze how human-made networks (power grids, transport and communication systems) can adapt to climate change. How can we enhance their robustness against the risk of systemic collapse? |
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.