Cosnet Lab Nov 2025, welcoming its new members.

Previous works showed that directionality within layers can enhance diffusion (e.g., superdiffusion & prime regime). Now, we demonstrate analytically and numerically that asymmetric interlayer links can both reproduce these regimes and, remarkably, lead to a novel phenomenon. 2/4

Now out: "Directionality-induced jamming in multiplex networks" (arxiv.org/abs/2510.22634). We uncover a previously unreported diffusion regime, termed directionality-induced jamming, in multiplex networks that arises solely from the directionality of interlayer couplings. (1/4)

Previous works showed that directionality within layers can enhance diffusion (e.g., superdiffusion & prime regime). Now, we demonstrate analytically and numerically that asymmetric interlayer links can both reproduce these regimes and, remarkably, lead to a novel phenomenon. (2/4)

Our framework demonstrates a scenario for facilitating the representability of deep neural networks through learning the underlying mechanism, which aims to steer applications for predicting complex behavior that learnable physical rules can drive. Kudos to my co-authors! 4/4

We evaluate the performance of our framework in predicting typical critical behavior in spreading dynamics on various synthetic and real-world networks. Our results show that governing rules can be learned effectively and significantly improve prediction accuracy. 3/4

More specifically, the learned governing rules further refine and guide the representative learning of neural networks from a series of dynamic graphs. This combination enables knowledge-based prediction for the critical behavior of dynamical networked systems 2/4

New MS: "Predicting the critical behavior of complex dynamic systems via learning the governing mechanisms" (arxiv.org/abs/2504.09622). We propose a framework to learn the rules that govern the dynamics of a system & apply it to study SIR dynamics & predict critical properties 1/3

Last of 2024: "Interplay of epidemic spreading and vaccine uptake under complex social contagion"(arxiv.org/abs/2412.11766). Here we investigate the interaction between disease dynamics (simple contagion), and human behavior in vaccine uptake (complex contagion). Results show a rich phase space.

The 2M€ investment in upgrading & expanding our HPC facilities is essentially completed. We have got a quite state-of-the-art "Agustina" supercomputer unit, which will allow doing our usual complex systems research + plenty of new projects in the AI domain. Exciting times ahead!

Now out: "Contagion dynamics on higher-order networks" (arxiv.org/abs/2402.14938). This is a focused review of the topic that also proposes a unified formalism covering most of the functional forms used for the spreading dynamics and discusses a roadmap for empirical validation.

Glad this work is now published, just before
@Micovar_ public PhD dissertation! See the paper for + details of our findings. Main take-home: older adult vaccination can reduce TB incidence in China if the vaccine protects already exposed individuals. www.frontiersin.org/journals/pub...

We placed the focus on studying the role of the adoption rate of DCT apps and the compliance of users in realistic populations. Our analysis confirmed that high levels of adoption are required but also revealed the equally key role of compliance in making DCT apps effective (2/2)

Latest out: "Characterizing the role of human behavior in the effectiveness of contact-tracing applications" (frontiersin.org/articles/10.33…). Here, we developed a model that allows exploring the impact of human behavior on the effectiveness of digital contact tracing (DCT) systems (1/2)

I am visiting Guido Caldarelli at Ca'Foscari University these days and giving today a lecture to students on disease dynamics. I am lucky enough to get an autographed copy of Guido's book!

Out at Nat Comms: nature.com/articles/s41.... We present a Bayesian framework to evaluate the compatibility of different vaccine descriptions with clinical trial outcomes unlocking impact forecasting from vaccines whose specific mechanisms of action are unknown.