I briefly survey several fascinating topics in networks and nonlinearity. I highlight a few
methods and ideas, including several of personal interest, that I anticipate to be especially …

We study an SEIQR (Susceptible–Exposed–Infectious–Quarantined–Recovered) model due
to Young et al.(2019) for an infectious disease, with time delays for latency and an …

Activity-driven networks (ADNs) have recently emerged as a powerful paradigm to study the
temporal evolution of stochastic networked systems. All the information on the time-varying …

A pandemic can wreak havoc in supply chains, as witnessed in the COVID-19 context. As
workers get infected, production level drops and demand from customers goes unfulfilled …

Network-based intervention strategies can be effective and cost-efficient approaches to
curtailing harmful contagions in myriad settings. As studied, these strategies are often …

Diseases spreading over humans and animals is a ubiquitous process that has attracted
much attention recently. To deeply explore the dynamics of the disease spread process on …

The authorship attribution is a problem of considerable practical and technical interest.
Several methods have been designed to infer the authorship of disputed documents in …

We analyze two alterations of the standard susceptible-infected-susceptible (SIS) dynamics
that preserve the central properties of spontaneous healing and infection capacity of a vertex …

The spread of excitations by Rydberg facilitation bears many similarities to epidemics. Such
systems can be modeled with Monte Carlo simulations of classical rate equations to great …

Understanding diffusive processes in networks is a significant challenge in complexity
science. Networks possess a diffusive potential that depends on their topological …