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).
An interactive journey to discover why a system is complex
A chapter about the math of multilayer networks
Two chapters about structure and dynamics of multilayer networks
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.
Understing systems robustness beyond network structure
Multiscale statistical physics of the pan-viral interactome unravels the systemic nature of SARS-CoV-2 infections
Data fusion of vaccination data with the global burden of disease
In italian, explaining how the source code of the cell and mRNA vaccine.
Bots are less central than verified accounts during contentious political events.
Understanding the latent geometry of empirical complex systems, topologically and functionally.
Modeling of epidemics spreading and social dynamics to understand the risk of outbreaks in Turkey.
CovMulNet19: a framework for Integrating Proteins, Diseases, Drugs, and Symptoms. A Network Medicine Approach to COVID.
Quantifying the risks of an infodemic in 127 countries with big data science.
Exploring complexity science and its applications through the eyes of leading experts
Resources, references and explanations about COVID19
Monitor the misinformation risk worldwide