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Containment, Avalanches and Optimisation in Spreading-processes

Total Cost €


EC-Contrib. €






 CAOS project word cloud

Explore the words cloud of the CAOS project. It provides you a very rough idea of what is the project "CAOS" about.

ignored    explosively    global    dynamic    outbreak    topology    boosting    heterogeneous    asymptotic    equilibrium    dynamics    cascading    society    drastic    area    instances    algorithmic    vaccines    networks    telecom    contain    allocation    abrupt    cooperative    epidemics    gain    deployment    techniques    contagion    charity    social    practical    provision    forming    decisions    optimal    warning    spreading    tiny    transitions    material    failures    distributing    message    solutions    avalanche    catastrophic    monitor    onset    picture    physics    british    passing    multiple    statistical    macroscopically    scientific    campaigns    pandemics    marketing    signals    critical    signs    period    outbreaks    manifestation    movements    ubiquitous    policy    promotion    spread    resource    blackouts    realistic    collaborate    modern    competitive    commercial    employing    lacking    advertising    beneficial    algorithms    optimisation    interplay    abruptly    epidemic    technological    service   

Project "CAOS" data sheet

The following table provides information about the project.


Organization address
postcode: B4 7ET

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Total cost 224˙933 €
 EC max contribution 224˙933 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2018
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2019
 Duration (year-month-day) from 2019-08-01   to  2021-07-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    ASTON UNIVERSITY UK (BIRMINGHAM) coordinator 224˙933.00


 Project objective

Spreading processes, such as cascading failure of technological networks, epidemic outbreak and contagion in social networks are ubiquitous and have a significant impact on the modern society. In many cases, transitions to large-scale blackouts or global pandemics occur abruptly due to tiny changes in system parameters; epidemics and social movements can spread out explosively, forming avalanche-like outbreaks in a very short period. The drastic transitions are beneficial for making global impact of boosting charity campaigns and commercial advertising but can also have catastrophic consequences when epidemics or failures spread to large part of a critical systems abruptly, without any early warning signals. Moreover, multiple cooperative of competitive spreading processes make the picture even more complex.

Previous work in this area focused on the asymptotic manifestation of the process and typically ignored the interplay between specific system topology and the dynamics. Methods to monitor, identify and control drastic transitions and outbreaks in heterogeneous realistic networks are lacking. In this project, we will investigate the signs for abrupt transitions and avalanche outbreaks both macroscopically and in specific instances, to gain insight into the conditions for their onset. We will develop methods to contain (or facilitate) the outbreaks by optimal deployment of resources, such as applying vaccines or distributing promotion material by employing the recently developed dynamic message passing techniques from statistical physics. We will collaborate with British Telecom to promote product marketing and service provision by using the new optimisation algorithms. This project will have significant impact on the scientific understanding of non-equilibrium spreading processes, provide algorithmic solutions for practical problems in specific instances, will support policy making decisions and offer optimal resource allocation for commercial marketing tasks.


year authors and title journal last update
List of publications.
2020 Bo Li, David Saad
Large deviation analysis of function sensitivity in random deep neural networks
published pages: 104002, ISSN: 1751-8113, DOI: 10.1088/1751-8121/ab6a6f
Journal of Physics A: Mathematical and Theoretical 53/10 2020-03-05

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The information about "CAOS" are provided by the European Opendata Portal: CORDIS opendata.

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