Experience

 
 
 
 
 
January 2019 – Present
London

Teaching Fellow

Queen Mary University of London

School of Electronic Engineering & Computer Science
 
 
 
 
 
October 2017 – October 2018
London

Enrichment Doctoral Student

The Alan Turing Institute

 
 
 
 
 
September 2016 – Present
London

Postgraduate Research Student

Queen Mary University of London

Complex Systems and Networks Research Group
 
 
 
 
 
September 2016 – December 2018
London

Computational Support Assistant

Queen Mary University of London

Dynamical Systems and Statistical Physics Research Group
 
 
 
 
 
May 2016 – September 2016
Turin

Researcher

ISI Foundation

Data Science Lab - Mathematics & Foundation of Complex Systems Group
 
 
 
 
 
September 2015 – April 2016
Bern

Data Science Intern

United Nations - Universal Postal Union

Selected Publications

Complex networks have been successfully used to describe the spreading of a disease in populations of interacting individuals. Conversely, pairwise interactions are often not enough to characterize processes of social contagion, such as opinion formation or the adoption of novelties, where more complex dynamics of peer influence and reinforcement mechanisms are at work. Here we introduce a high-order model of social contagion in which a social system is represented by a simplicial complex and the contagion can occur, and with different transmission rates, not only over the links but also through interactions in groups of different sizes. Numerical simulations of the model on synthetic simplicial complexes highlight the emergence of novel phenomena such as the appearance of an explosive transition induced by the high-order interactions. We show analytically that the transition is discontinuous with the formation of a bistable region where healthy and endemic states co-exist. Our results represent a first step to understand the role of high-order interactions in complex systems
2018
Preprint

We introduce a model for the emergence of innovations, in which cognitive processes are described as random walks on the network of links among ideas or concepts, and an innovation corresponds to the first visit of a node. The transition matrix of the random walk depends on the network weights, while in turn the weight of an edge is reinforced by the passage of a walker. The presence of the network naturally accounts for the mechanism of the adjacent possible, and the model reproduces both the rate at which novelties emerge and the correlations among them observed empirically. We show this by using synthetic networks and by studying real data sets on the growth of knowledge in different scientific disciplines. Edge-reinforced random walks on complex topologies offer a new modeling framework for the dynamics of correlated novelties and another example of co-evolution of processes and networks.
In Physical Review Letters, 2018
Preprint PDF DOI Press

Recent Publications

PDF DOI

Complex networks have been successfully used to describe the spreading of a disease in populations of interacting individuals. …
Preprint

We introduce a model for the emergence of innovations, in which cognitive processes are described as random walks on the network of …
Preprint PDF DOI Press

Activities

Teaching

I am giving lectures on Network Science within the School of Electronic Engineering & Computer Science (QMUL):

  • 2018⁄2019 Network Modeling and Performance (ECS724U/P).

I’ve been Teaching Assistant for the following courses at QMUL:

  • 2016⁄2017 Introduction to Statistics (MTH4106/MTH4206).
  • 2016⁄2017 Network Modeling and Performance (ECS724U/P).

Referee Activity

I’ve been a reviewer for the journals:

Chaos, EPJ Data Science, Physical Review E, Scientific Reports, Europhysics Letters, Chaos Solitons & Fractals.

Scholarships, Grants & Awards

  • 2017 Travel Grant for the Symposium on The Future of Urban Networks Research, Ghent University.
  • 2017 Turing PhD Enrichment Scolarship, The Alan Turing Institute.
  • 2017 Travel Grant for the Summer School on Methods for Computational Social Science, GESIS.
  • 2016 Research Studentship Queen Mary Principal’s Award, QMUL.

Conferences, Schools and Symposia

  • Oct 2018 2nd Network Science Workshop

    London, UK.

  • Sep 2018 Conference on Complex Systems 2018

    Thessalokini, GR.

  • Jun 2018 NetSci 2018 International Conference on Network Science

    Paris, FR.

  • Feb 2018 BIFI International Conference 2018 on Complexity, Networks and Collective behaviour

    Zaragoza, ES.

  • Sep 2017 European Symposium Series on Societal Challenges in Computational Social Science

    London, UK.

  • Sep 2017 Symposium on The Future of Urban Networks Research

    Ghent University, BE.

  • Jul 2017 Summer School on Methods for Computational Social Science

    Sant’Antioco, IT.

  • Jun 2017 Cambridge Networks Day 2017

    University of Cambridge, UK.

  • Jan 2017 Mathematics and Economics of Energy Markets

    National Grid, Wokingham, UK.

  • Oct 2015 UN Conference on Global Addressing

    UPU, Bern, CH.

  • Nov 2015 UN Global Conference on Trade facilitation

    UPU, Bern, CH.

Contact

  • iacopo.iacopini
  • Queens Building W313, Queen Mary University of London, London, E1 4NS, UK