Research at the edge of statistical physics, applied math and computer science

I study 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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Since November 2022 I curate the Complexity Thoughts newsletter, where you can subscribe for free by clicking here. Find me on Mastodon and Twitter.

With my Lab, I focus on some fields of interests that can be summarized in the following three pillars:

>> 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?
>> Network medicine

We study biological networks and the coupling between human behavior and the spread of infectious diseases. Can we improve health from acting on networks? How climate change will influence the emergence of infectious diseases?
>> Statistical physics of information dynamics

We study the role of information in shaping structure and behavior of complex systems, offering new perspectives on their function and design. Can we design a complex system from first principles?

Latest news from the lab

Our fields of interest

  • Multilayer analysis of structure and function, with focus on brain diseases such as Alzheimer's, Attention Deficit Hyperactivity Disorder, Autism and Schiozphrenia. <p><a class='btn btn-primary btn-small' href='systems_biology.php'>Learn more »</a></p>

    Human Brain

  • Multilayer modeling and analysis of omics, with the aim of integrating systems for better understanding life and human diseases. <p><a class='btn btn-primary btn-small' href='systems_biology.php'>Learn more »</a></p>

    Life and Disease

  • Big-data-driven multilayer modeling of complex dynamics to drive information awareness and contain the spreading of epidemics diseases. <p><a class='btn btn-primary btn-small' href='comp_epidemiology.php'>Learn more »</a></p>

    Computational Epidemiology

  • Multilayer analysis of online social activity and collective attention, computational modeling of individuals' behavior. <p><a class='btn btn-primary btn-small' href='comp_socialscience.php'>Learn more »</a></p>

    Computational Social Science

  • Big-data-driven multilayer modeling of (smart) urban systems and human mobility. <p><a class='btn btn-primary btn-small' href='human_mobility.php'>Learn more »</a></p>

    Transportation and Mobility

  • Multilayer risk analysis of integrated social, political, economical, technological and ecological systems, to support policy and decision-making.

    Global Risks and Policy

  • Blockchain-based solutions for the scientific environment, from peer-review system to replicability and reproducibility.

    Blockchain-based Applications

  • Development of advanced statistical and visualization tools for the analysis of data generated by complex systems.

    Multivariate Analysis and Viz

Hint: Click on one image and look for the 'Learn more' button, to know more details about each topic in context.

Theoretical Framework for Applied Research

Network Structure

Theoretical advance on the representation of complex networks for modeling empirical complex systems, identifying central/influential units and determine the underlying meso-scale organization.

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Complex Dynamics

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.

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Network Information

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.

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Network Geometry

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.

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