Alexandre Bovet, Carlo Campajola, Francesco Mottes, Valerio Restocchi, Nicolò Vallarano, Tiziano Squartini and Claudio J. Tessone
The Evolving Liaisons between the Transaction Networks of Bitcoin and Its Price Dynamics
JPS Conference Proceedings (2023)

Benjamin Steinegger, Iacopo Iacopini, Andreia Sofia Teixeira, Alberto Bracci, Pau Casanova-Ferrer, Alberto Antonioni and Eugenio Valdano
Non-selective distribution of infectious disease prevention may outperform risk-based targeting
Nature Communications (2022)



Ethics in rotten apples: A network epidemiology approach for active cyber defense 
(Bonacina, Echegoyen, Escribano, Krellner, Nerini, Shanaz, Teixeira, Aleta)

Spaces of innovation and venture formation: the case of biotech in the United Kingdom 
(Marzolla, Nowak, Sahasrabuddhe, Singh, Straccamore, Zhivkoplias, Arcaute)

Unraveling higher-order dynamics in collaboration networks 
(Abella, Birello, Di Gaetano, Ghivarello, Sabhahit, Sirocchi, Fernandez-Gracia)

Beyond Active Engagement: The Significance of Lurkers in a Polarized Twitter Debate 
(Baqir, Chen, Diaz-Diaz, Kyak, Louf, Morini, Pansanella, Torricelli, Galeazzi)

Discriminatory or Samaritan — which AI is needed for humanity? An Evolutionary Game Theory Analysis of Hybrid Human-AI populations 
(Booker, Miranda, Moreno Lopez, Ramos Fernandez, Reddel, Widler, Zimmaro, Antonioni, Anh Han)

Disruption of outdoor activities caused by wildfire smoke shapes circulation of respiratory pathogens 
(Arregui Garcia, Ascione, Pera, Stocco, Wang, Valdano, Pullano)

Temporal network-based analysis of fluid flow with applications to marine ecology 
(Acharya, Aguilar, Dall’Amico, Nicolaou, Tong, Ser-Giacomi)


Marton Karsai
Temporal networks: representation and modeling

Jesús Gómez-Gardeñes

James Watson
Society needs a software update: Measuring, predicting and managing the complexity of socio-environmental systems

(Tutorial: Fernando Diaz-Diaz)
Structure and dynamics of signed networks

(Tutorial: Manuel Miranda)
Introduction to Otree and graph representation using Cytoscape

(Tutorial: Max Reddel)
Decision-Making under Deep Uncertainty: Steering Through the Complex Storm

(Tutorial: Rasha Shanaz)
Build your own reservoir computer from scratch with ReservoirPy


MÁRTON KARSAI (lecturer): Márton Karsai is an Associate Professor at the Department of Network and Data Science at the Central European University in Vienna and a researcher at the Rényi Institute of Mathematics in Budapest. He is a network scientist with research interest in human dynamics, computational social science, and data science, especially focusing on heterogeneous temporal dynamics, spatial and temporal networks, socioeconomic systems and social contagion phenomena. He is an expert in analysing large human behavioural datasets and in developing data-driven models of social phenomena.

JESÚS GÓMEZ-GARDEÑES (lecturer): Jesús is an Associate Professor (Profesor Titular) in the Department of Condensed Matter Physics of the University of Zaragoza (Spain). He leads the Group of Theoretical & Applied Modeling (GOTHAM lab) at the Institute of Biocomputation and Physics of Complex Systems (BIFI).

JAMES WATSON (lecturer): James Watson is an Associate Professor in the College of Earth, Ocean and Atmospheric Sciences at Oregon State University. He and his lab develop mathematical theory and computational methods for application in the domains of ecology, geography, oceanography and sustainability science. He takes inspiration from complex adaptive systems more generally, and in addition to his work on socio-environmental systems he conducts research into financial markets, resource economics and sports data analytics. He is interested in learning from all complex systems to help improve our ability to live sustainably. Previously, he received his PhD in Marine Science from the University of California Santa Barbara, and spent time as a post-doctoral researcher at Princeton University and as a research scientist at the Stockholm Resilience Centre. Hen was the recipient of a DARPA Young Faculty Award and the Oceanography Society’s Early Career Award for his interdisciplinary work. 

ALBERTO ALETA (tutor): University of Zaragoza, Zaragoza, Spain.

ELSA ARCAUTE (tutor): UCL, London, UK

JUAN FERNANDEZ-GARCIA (tutor): IFISC, Palma de Mallorca, Spain

ALESSANDRO GALEAZZI (tutor): Ca’ Foscari University of Venice, Venice, Italy

THE ANH HAN (tutor): University, Middlesbrough, England, UK

GIULIA PULLANO (tutor): Georgetown University, Washington, DC, USA

ENRICO SER-GIACOMI (tutor): IFISC, Palma de Mallorca, Spain






PERE COLET (Local organizer)
JOSE RAMASCO (Local organizer)

ROME 2020


Due to the pandemic, the Complexity72h 2020 edition has been cancelled.


Due to the pandemic, the Complexity72h 2020 edition has been cancelled.









ELSA ARCAUTE: Elsa is a physicist with a masters in Mathematics and a PhD in Theoretical Physics from the University of Cambridge, UK. She is an Associate Professor in Spatial Modelling and Complexity at the Centre for Advanced Spatial Analysis (CASA), and Co-Investigator of an EPSRC grant on Digital Economies, and a MacArthur funded research project on Smart Cities. website

ALAIN BARRAT:  Alain obtained his PhD in theoretical physics at the university of Paris VI. He is currently CNRS senior researcher at the Centre de Physique Théorique in Marseille, of which he is also deputy director. He is also Specially Appointed Professor at Tokyo Institute of Technology (Japan), vice-president of the Complex Systems Society, and board member of the NetSci Society. His research focuses on complex networks and temporal networks, with many interdisciplinary connections. website

ANA BENTO: Ana is an Assistant Professor at Indiana University in Epidemiology & Biostatistics, School of Public Health & the EEB department. She is an eco-epidemiologist with a focus on ecology and evolution of infectious diseases. She earned her Ph.D. in Ecology & Evolution at Silwood Park, Imperial College London. Her research seeks to understand the dynamics of biological populations and epidemics, focusing on how to bring experimental and observational data together with mathematical theory. website

ELISA OMODEI: Elisa holds a PhD in Applied Mathematics for the Social Sciences from the École Normale Supérieure of Paris. She currently works in the Research, Assessment and Monitoring division of the UN World Food Programme. She also serves as Vice-President Secretary of the Complex System Society. Her research focuses on complex networks and data science for development and humanitarian response. website

LETO PEEL:  Leto has over 10 years of experience in theoretical and applied machine learning research in both academia and industry. His current research interest is in developing statistical methods for analysing complex networks. He has worked on many interdisciplinary research projects, collaborating with experts from a diverse variety of domains. His industry collaborations have included Airbus, BAE Systems and London MET Police and has collaborated with a variety of academic institutions. website

LIUBOV TUPIKINA:  Liubov has been working in mathematics and statistical physics: she is interested in graph theory, random walks, dynamical systems, matrix theory and its applications. She has been working on projects applying stochastic processes and statistical learning to analyze trajectories and time-series data. Currently she is a researcher at Bell labs (Saclay, France) and CRI (Paris, France). Before she has been working at Ecole Polytechnqiue (France), Humboldt University in Marie-Curie project along with Potsdam Climate Institute (Germany), IFISC (Spain). website


LUCCA 2019


Community Detection in the Hyperbolic Space 
(Bruno, Sousa, Gursoy, Serafino, Vianello, Vranić, Boguñá)

Evaluating the impact of PrEP on HIV and gonorrhea on a networked population of female sex workers 
(Bernini, Blouzard, Bracci, Casanova, lacopini, Steinegger, Teixeira, Antonioni, Valdano)

Inside the Echo Chamber: Disentangling network dynamics from polarization 
(Balsamo, Gelardi, Han, Rama, Samantray, Zucca, Starnini)

Maximum entropy approaches for the study of triadic motifs in the Mergers & Acquisitions network 
(Adam, Garlaschi, Lin, Piaggesi, Barigozzi, Gabrielli, Mastrandrea)

Shall we turn off the media? Global information can destroy local cooperation in the one-dimensional ring 
(Aydin, Biondo, Gupta, Ivaldi, Lipari, Lozano, Parino, Bilancini, Boncinelli, Capraro)

Simplex2Vec embeddings for community detection in simplicial complexes 
(Billings, Hu, Lerda, Medvedev, Mottes, Onicas, Santoro, Petri)


Susanna Manrubia
Viral war games: When evolution defeats imagination
Viruses count amongst the most amazing organisms on Earth regarding their evolutionary and adaptive abilities. They resort to several different forms of coding information in their genomes; together with an array of different mutational mechanisms, they have succeeded in infecting all cellular organisms and in escaping any antiviral strategy (natural or artificial). We will present two examples of viral adaptive strategies that can be formally addressed: the complex population response to combinations of antiviral drugs and the advantages of viruses with multipartite genomes. Finally, we will briefly discuss the origin of viruses and the role they may have played in the evolution of life.

Fabrizio Lillo
Dynamical models of temporal networks
Many complex systems can be described as temporal networks, i.e. networks where links appear and disappear with time. Given the high dimensionality of the problem, suitable models are needed, especially if one is interested in parameter or hidden variable estimation, link forecasting, and analytical modelling the propagation of a signal on the network. In this lecture I will present some recent advancement in the field, introducing stationary and non-stationary models with application to financial and social temporal networks.

Marián Boguñá
Network geometry. A geometric approach to complex networks
The main hypothesis of the network geometry program states that the architecture of real complex systems has a geometric origin. In a nutshell, the idea is that the elements of a complex system can be characterized by their positions in some underlying metric space so that the observable network topology —abstracting their patterns of interactions— is a reflection of their distances in this space. This simple idea has led to the development of a very general framework able to explain the most ubiquitous topological properties of real complex networks, namely, degree heterogeneity, the small-world property, and high levels of clustering. Network geometry is also able to explain in a very natural way non-trivial properties of real networks, like their self-similarity and community structure, their navigability properties, and is the basis for the definition of a renormalization group in complex networks. The same framework has also been successfully extended to weighted networks and multiplexes. In this lecture, I will review the work done in this field of research during the last ten years and discuss the applications of network geometry to many open problems in network science.

Claudio Tessone
A complex systems approach to cryptocurrencies
Cryptocurrencies are possible because their public ledgers allow the storage of trustworthy information without the pre-requisite of trust between system participants. However, for this property to be preserved, ‘who’ writes these data into the ledger must be acceptable to all. Thus, centralisation of any kind is against the core principle of blockchain-based systems. Cryptocurrencies are the most widely adopted incarnation of blockchains. They are plagued with economic incentives, many of them obvious, some others put inadvertently. In this presentation we will review different links between microscopic agent behaviour and macroscopic emergent properties of cryptocurrencies.
The lecture consists of three parts: Wealth dynamics, financial markets and dark markets. In the first part of the lecture, we will explain the increasing concentration on wealth (and power!) in different cryptocurrencies, and link it to underlying design principles. In the second, we will explain the relationship between endogenous activity in cryptocurrencies and price dynamics with respect to fiat currencies. Finally, the third part will delve into the circulation (and relative size!) of illegal trades in cryptocurrencies.

Multiresolution Filterbanks to Enhance Signal Contrast 
(Speaker: Jacob Billings)
The tutorial explores the use of wavelet filters to enhance feature detection among time series. Wavelet filters are especially useful at localizing deviations from ongoing dynamics. The tutorial will demonstrate the use of several wavelet filtration schema–including continuous, discrete, and bi-orthogonal–to enhance data-driven feature detection in time-series.

Unravelling the topological arrangements and selected reaction parameters from global measurements of an extended neural model
(Speaker: Ihusan Adam)
Living brains show immensely complex dynamics that are often modelled by ensembles of simple neuron models connected through a network of intricate structure. The complexity displayed by these systems stem from the topology of the network support. To gain an insight into this problem, we propose and test a procedure that is aimed at reconstructing the a priori unknown architecture of the embedding network. To this end we consider and extended model of Leaky-Integrate and Fire (LIF) neurons with short-term plasticity. The neurons are coupled to directed network and display a level of heterogeneity in the associated current a, which dictates the  ring regime in which a neuron is operating in. The aim of the method is to recover the distribution of connectivity k ̃ of the underlying networks as well as the distribution of the assigned a. Our approach to the inverse problem makes use of the celebrated Heterogenous Mean-Field (HMF) approximation to rewrite the dynamics of the system by splitting the types of neurons into classes which re ect the associated a and in-degree k ̃. The HMF reduction scheme allows us to in essence, create a mesh on the space de ned by the variables a and k ̃ in such a way that all possible neurons fall within this space. The two sought distributions of P(a) and P(k ̃) are then the correct solutions that sum the classes of neurons to reproduce the global  eld that was obtained by simulating the original model. We have tested this on synthetic data, where the global  eld was generated by a random network and a bell-shaped distribution of currents, and here the method captures the two distributions remarkably well and manages to almost exactly reproduce the global field.

The Origins of Social Balance in Signed Networks
(Speaker: Sofia Teixeira Monteiro)
Social media often reveals a complex interplay between positive and negative ties. And real online social networks are proven to show high social balance. Yet, the origin of such complex patterns of interaction remains largely elusive. In this work we study how third parties may sway our perception of others. We build a model of peer-influence relying on the analysis of all triadic relations taking into account the relations with common friends. We show that this simple peer-influence mechanism, based on balance theory of social sciences, is able to promptly increase the social balance of a signed network.



Marián BOGUÑÁ (lecturer/tutor): Marián Boguñá is an associate professor and Icrea Academia researcher at the Dept of Condensed Matter Physics, University of Barcelona, Spain. Currently, his main research interests focus on Complex Systems and Complex Networks, two exciting and multidisciplinary fields of research that apply Statistical Physics techniques to the understanding of the many networked systems around us. website

Fabrizio LILLO (lecturer): Fabrizio Lillo is full Professor of Mathematical Methods for Economics, Finance, and Actuarial Sciences at the University of Bologna, Italy. website

Susanna MANRUBIA (lecturer): Susanna Manrubia is a research leader at the National Biotechnology Center (CSIC), Madrid, Spain. website

Claudio TESSONE (lecturer/tutor): Claudio J. Tessone is assistant professor at the Dept of Business Administration of the University of Zurich. He applies network analysis to socio-economical systems. website

Ennio BILANCINI (tutor): Ennio Bilancini is a professor of economics at IMT School of Advanced Studies, Lucca. He has conducted research in the areas of cognitive and behavioral economics, economic theory, (evolutionary) game theory, microeconomics, social economics, subjective well-being and welfare. He is currently interested (and prompt to supervise students interested) in the evolution of prosociality, evolutionary selection of game equilibria, measurement of strategic skills, measurement of bounded rationality, dual process interactive decision-making, economics of social status and social norms, social determinants of subjective well-being. website

Valerio CAPRARO (tutor): Valerio is a senior lecturer in economics at Middlesex University of London, UK. He combines math models and behavioral experiments to understand how people solve cooperative tasks, with the goal of helping institutions to create more collaborative societies. website

Andrea GABRIELLI (tutor): Andrea Gabrielli is a permanent researcher at the Institute of Complex Systems (ISC) of the Italian CNR. He works in statistical physics, fractal growth phenomena, percolation, self-organized criticality, application of statistical physics to cosmological and gravitational problems. His main present interest focuses on the applications of complex networks and stochastic processes to economy and brain science. website

Laetitia GAUVIN (tutor): Laetitia Gauvin is a research leader at ISI Foundation, Turin, Italy. website

Giovanni PETRI (tutor): Giovanni Petri is a research leader at ISI Foundation, Turin, Italy. website

Michele STARNINI (tutor): Michele Starnini is a researcher at ISI Foundation, Turin, Italy. website

Eugenio VALDANO (tutor): Eugenio is a postdoc at University of California, Los Angeles, USA. He is a physicist and epidemiologist. He works in infectious disease modeling. His current focus is the HIV epidemic in Sub-Saharan Africa. website 







LUCCA 2018


Altered modularity and disproportional integration in functional networks are markers of abnormal brain organization in schizophrenia 
(Cinelli, Echegoyen, Oliveira, Orellana, Gili)

Dynamics of new strain emergence on a temporal network
(Chakraborty, Hoffmann, Leguia, Nolet, Ortiz, Prunas, Zavojanni, Valdano, Poletto)

Maximum entropy approach to link prediction in bipartite networks
(Baltakiene, Baltakys, Cardamone, Parisi, Radicioni, Torricelli, van Lidth de Jeude, Saracco)

Network-based indicators of Bitcoin bubbles
(Bovet, Campajola, Lazo, Mottes, Pozzana, Restocchi, Saggese, Vallarano, Squartini, Tessone)

Network sensitivity on systemic risk
(Di Gangi, Lo Sardo, Macchiati, Minh, Pinotti, Ramadiah, Wilinski, Cimini)


Fosca Giannotti (lecture)
Big Data for understanding human dynamics: the power of networks

Claudio Tessone  (lecture)
A complex systems perspective to blockchain-based systems

Chiara Poletto  (lecture)
Introduction to network epidemiology

Guido Caldarelli  (lecture)
Application of statistical physics to finance

Paolo Barucca  (tutorial)
Network models of systemic risk

Marcos Oliveira  (tutorial)
Performing embarrassingly parallel data analysis in Python using IPyparallel and Pandas

Ruggiero Lo Sardo (tutorial)
Web visualization of small scale complex networks

Alexandre Bovet  (tutorial)
Uncovering memory patterns in temporal networks with higher-order Markov models

Tommaso Radicioni  (tutorial)
How to use Gephi? A short introduction to network analysis and visualization


GUIDO CALDARELLI (lecturer): Guido Caldarelli is full professor of physics at IMT Lucca, and LIMS fellow. He is vice-president of the Complex Systems Society, and in the board of the statistical and nonlinear physics division of the European Physical Society. His research interests involve structure of networks, financial networks, and multiplex networks. website

FOSCA GIANNOTTI  (lecturer): Fosca Giannotti is a senior researcher at the Information Science and Technology Institute of the National Research Council at Pisa, Italy, where she leads the Knowledge Discovery and Data Mining Laboratory. Her current research interests include data mining query languages, knowledge discovery support environment, web-mining, spatio-temporal reasoning, spatio-temporal data mining, and privacy preserving data mining. website

CHIARA POLETTO  (lecturer): Chiara Poletto is a researcher at INSERM (French National Institute of Health and Medical Research). She studies emerging pathogens and disease ecology. She applies network physics and complex system approaches to reach a theoretical understanding of the interplay between human behaviour and infection propagation, using data-driven computational models. Her goal is to provide a quantitative assessment forecast of the epidemic evolution. website

CLAUDIO J. TESSONE  (lecturer): Claudio J. Tessone is assistant professor at the Dept of Business Administration of the University of Zurich. He applies network analysis to socio-economical systems. website

GIULIO CIMINI  (tutor): Giulio Cimini is assistant professor in Quantitative Analysis and Modeling of Complex Economical and Financial Systems at IMT Lucca. website

ANGELO FACCHINI  (tutor): Angelo Facchini is Assistant Professor at IMT Lucca. His research interests are in the field of nonlinear time series analysis, complex systems and data science with applications to biophysical phenomena, markets, infrastructural water and energy networks, urban sustainability, and megacities. website

TOMMASO GILI  (tutor): Tommaso Gili currently works at the NETWORKS Complex Networks Research Unit, IMT School for Advanced Studies Lucca. Tommaso does research in Polymer Chemistry, Physical Chemistry and Biophysics. website

FABIO SARACCO  (tutor): Fabio Saracco is assistant professor at IMT Lucca, since October 2015, when he joined the NETWORKS research unit. website