Guilherme Ferraz de Arruda

Team Leader

CENTAI Institute


I am a team leader at Centai. My interests are nonlinear dynamics and stochastic processes on top of complex networks and structured populations. More specifically, I am focusing on epidemic and rumor spreading in single and multilayer systems. Additionally, I am concerned about the structural characterization of multilayer networks, mainly through spectral theory. Recently, I am also involved in the study of higher-order interactions and hypergraphs, both from the structural and dynamics viewpoints. If you need further information, please don't hesitate to contact me.


  • Complex networks
  • Multilayer networks
  • Hypergraphs
  • Higher-order structures
  • Spreading processes
  • Stochastic process
  • Non-linear dynamics
  • Network spectra


  • Ph.D in Computer Science and applied Mathematics, 2017

    ICMC - Universidade de São Paulo

  • MsC in Computer Science and applied Mathematics, 2013

    ICMC - Universidade de São Paulo

  • Specialization in Digital Systems, 2011

    EESC - Universidade de São Paulo

  • Specialization in Control Theory, 2011

    EESC - Universidade de São Paulo

  • Electrical engineering, 2011

    EESC - Universidade de São Paulo

Recent Publications

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Multistability, intermittency and hybrid transitions in social contagion models on hypergraphs

Although ubiquitous, interactions in groups of individuals are not yet thoroughly studied. Frequently, single groups are modeled as …

From subcritical behavior to a correlation-induced transition in rumor models

Rumors and information spreading emerge naturally from human-to-human interactions and have a growing impact on our everyday life due …

Modeling how social network algorithms can influence opinion polarization

The study of the dynamics of opinion formation and transmission in social networks has attracted lots of attention. Here, we propose a …

The physics of higher-order interactions in complex systems

Complex networks have become the main paradigm for modelling the dynamics of interacting systems. However, networks are intrinsically …

Social contagion on higher-order structures

In this Chapter, we discuss the effects of higher-order structures on SIS-like processes of social contagion. After a brief …

Contrastes Entre Interesses Individuais e Coletivos: Uma Discussão Sob a Ótica da Epidemiologia Matemática (Portuguese)

A pandemia de coronavírus tem criado um ambiente completamente anômalo, evidenciando diversos aspectos da nossa sociedade e gerando …

Phase transitions and stability of dynamical processes on hypergraphs

Hypergraphs naturally represent higher-order interactions, which persistently appear in social interactions, neural networks, and other …

Evolutionary Dynamics of Higher-Order Interactions

We live and cooperate in networks. However, links in networks only allow for pairwise interactions, thus making the framework suitable …

Universality of eigenvector delocalization and the nature of the SIS phase transition in multiplex networks

Universal spectral properties of multiplex networks allow us to assess the nature of the transition between disease-free and endemic …

Data-driven contact structures: from homogeneous mixing to multilayer networks

The modeling of the spreading of communicable diseases has experienced significant advances in the last two decades or so. This has …

Social contagion models on hypergraphs

Our understanding of the dynamics of complex networked systems has increased significantly in the last two decades. However, most of …

Comparison of Different Spike Train Synchrony Measures Regarding Their Robustness to Erroneous Data From Bicuculline-Induced Epileptiform Activity

As synchronized activity is associated with basic brain functions and pathological states, spike train synchrony has become an …

Impact of the distribution of recovery rates on disease spreading in complex networks

We study a general epidemic model with arbitrary recovery rate distributions. This simple deviation from the standard setup is …

Layer degradation triggers an abrupt structural transition in multiplex networks

Network robustness is a central point in network science, both from a theoretical and a practical point of view. In this paper, we show …

A polynomial eigenvalue approach for multiplex networks

We explore the block nature of the matrix representation of multiplex networks, introducing a new formalism to deal with its spectral …