Network Robustness and Resilience
How can we measure the response of a complex network to failures and targeted interventions, and identify the structures that make it fragile or resilient?
Highlights
Understanding network robustness
How much disruption can a complex network withstand, and how can the few units whose loss fragments it be found?
The layered structure of global trade
How do commodity and industry layers organise international trade, and how do production shocks travel through it?
Research focus
Failures and targeted interventions can change the connectivity and function of a complex system. We study theoretical and computational methods for describing that response, with particular attention to network dismantling: identifying a small set of nodes or edges whose removal fragments a network.
This work includes comparisons of dismantling methods, machine-learning approaches to structural intervention and indicators that anticipate network disintegration.
Selected publications
- Robustness and resilience of complex networks, Nature Reviews Physics (2024)
- Machine learning dismantling and early-warning signals of disintegration in complex systems, Nature Communications (2021)
- Latent Geometry-Driven Network Automata for Complex Network Dismantling, ICLR (2026)
Code and data
The network dismantling review resource collects implementations, benchmark networks and reproducibility material associated with the 2024 review.