[info per studenti]

Link alla p
agina del corso

Fondamenti di automatica

(Ing. Matematica, L, 10 cfu, 2 sem)

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Complessità nei sistemi e nelle reti

(LM, 5 cfu, 1 sem, 2 emisem)

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Dinamica dei sistemi complessi

(LM, corso integrato, 5+5 cfu, 1 sem)

[info per studenti delle lauree magistrali]

Se siete interessati a studi di carattere generale riguardanti la dinamica dei sistemi complessi e le loro applicazioni, in particolare a temi quali la dinamica non lineare, il caos, le reti complesse, i sistemi adattativi, potete considerare di inserire nel vostro piano di studi qualcuno di questi corsi, attivi nell'a.a. 2016/17 presso il Campus Leonardo:

Teoria dei sistemi (Dinamica non lineare) (5 cfu, 1 sem, 1 emisem), docente Sergio Rinaldi
Systems theory (Nonlinear dynamics) (5 cfu, 1 sem, 1 emisem), docente Fabio Dercole
Complessità nei sistemi e nelle reti
(5 cfu, 1 sem, 2 emisem), docente Carlo Piccardi

Dinamica dei sistemi complessi
(5+5 cfu, 1 sem),
corso integrato

Per qualunque informazione in merito a questi corsi sieti invitati a rivolgervi ai rispettivi docenti.

Last update: May 22, 2018

Carlo Piccardi

DEIB - Dipartimento di Elettronica, Informazione e Bioingegneria
Politecnico di Milano
Piazza Leonardo da Vinci 32
20133 Milano, Italy

tel (++39) 02 2399 3566
fax (++39) 02 2399 3412
e-mail carlo.piccardi@polimi.it
web page http://home.deib.polimi.it/piccardi/

Click here for details on recent research activities (some with codes and data available).

Check the list of my publications on peer reviewed journals (or visit my Google Scholar page).

    [research highlights]
M. Bastos, C. Piccardi, M. Levy, N. McRoberts, and M. Lubell, Core-periphery or decentralized? Topological shifts of specialized information on Twitter, Social Networks, 52, 282-293, 2018. [doi]

In this paper we investigate shifts in Twitter network topology resulting from the type of information being shared. We identified communities matching areas of agricultural expertise and measured the core-periphery centralization of network formations resulting from users sharing generic versus specialized information. We found that centralization increases when specialized information is shared and that the network adopts decentralized formations as conversations become more generic. The results are consistent with classical diffusion models positing that specialized information comes with greater centralization, but they also show that users favor decentralized formations, which can foster community cohesion, when spreading specialized information is secondary.
C. Piccardi, M. Riccaboni, L. Tajoli, and Zhen Zhu, Random walks on the world input–output network, Journal of Complex Networks, 6, 187-205, 2018 [doi]

Modern production is increasingly fragmented across countries.To disentangle the world production system at sector level, we use the World Input–Output Database to construct the World Input–Output Network (WION) where the nodes are the individual sectors in different countries and the edges are the transactions between them. In order to explore the features and dynamics of the WION, in this article we detect the communities in the WION and evaluate their significance using a random walk Markov chain approach. Our results contribute to the recent stream of literature analysing the role of global value chains in economic integration across countries, by showing global value chains as endogenously emerging communities in the world production system, and discussing how different perspectives produce different results in terms of the pattern of integration.
F. Calderoni, D. Brunetto, and C. Piccardi,
Communities in criminal networks: A case study,
Social Networks, 48, 116-125, 2017. [doi]

Criminal organizations tend to be clustered to reduce risks of detection and information leaks. Yet, the literature exploring the relevance of subgroups for their internal structure is so far very limited. The paper applies methods of community analysis to explore the structure of a criminal network representing the individuals' co-participation in meetings. It draws from a case study on a large law enforcement operation (``Operazione Infinito'') tackling the 'Ndrangheta, a mafia organization from Calabria, a southern Italian region. The results show that the network is indeed clustered and that communities are associated, in a non trivial way, with the internal organization of the 'Ndrangheta into different ``locali'' (similar to mafia families). Furthermore, the results of community analysis can improve the prediction of the ``locale'' membership of the criminals (up to two thirds of any random sample of nodes) and the leadership roles (above 90% precision in classifying nodes as either bosses or non-bosses). The implications of these findings on the interpretation of the structure and functioning of the criminal network are discussed.


I am Full Professor at Politecnico di Milano. My teaching activity is in the area of complex systems and networks, dynamical systems and automatic control, both to undergraduate and graduate students of the Politecnico schools of engineering. I also teach in the PhD program of my Department (DEIB), mostly in the area of complex systems.

My research interests are focused on several topics concerning complex systems. Some recent areas of research are:

  • Structural properties of networks, with applications in economics, finance, and social sciences;
  • Spreading processes on complex networks;
  • Synchronization of networks of dynamical systems;
  • Reduced models for nonlinear systems, and their use for solving control and parameter estimation problems; 
  • Application of optimal control techniques to nonlinear systems; 
  • The use of numerical methods for bifurcation analysis of nonlinear systems, including continuation methods and harmonic-balance techniques; 
  • The analysis of structural properties of cooperative systems.