[info per studenti]


Link alla p
agina del corso

Fondamenti di automatica

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

Link alla pagina del corso
ComplessitÓ nei sistemi e nelle reti

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


Link alla pagina del corso
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. 2015/16 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
ComplessitÓ 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 31, 2016


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/




    [info]
5th International Workshop COMPLEX NETWORKS & their APPLICATIONS
Milan, Italy, 30 November - 2 December 2016 (tutorials: 29 November)
http://www.complexnetworks.org/

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

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

    [research highlights]
G. Berlusconi, F. Calderoni, N. Parolini, M. Verani, and C. Piccardi,
Link prediction in criminal networks: A tool for criminal intelligence analysis
,

PLoS ONE
, 11(4): e0154244, 2016.
[doi]




The problem of link prediction has recently received increasing attention from scholars in network science. In social network analysis, one of its aims is to recover missing links, namely connections among actors which are likely to exist but have not been reported because data are incomplete or subject to various types of uncertainty. In the field of criminal investigations, problems of incomplete information are encountered almost by definition, given the obvious anti-detection strategies set up by criminals and the limited investigative resources. In this paper, we work on a specific dataset obtained from a real investigation, and we propose a strategy to identify missing links in a criminal network on the basis of the topological analysis of the links classified as marginal, i.e. removed during the investigation procedure. The main assumption is that missing links should have opposite features with respect to marginal ones. Measures of node similarity turn out to provide the best characterization in this sense. The inspection of the judicial source documents confirms that the predicted links, in most instances, do relate actors with large likelihood of co-participation in illicit activities.
I. Cingolani, C. Piccardi, and L. Tajoli, Discovering preferential patterns in sectoral trade networks,
PLoS ONE, 10(10)
, e0140951, 2015. 
[doi]

We analyze the patterns of import/export bilateral relations, with the aim of assessing the relevance and shape of "preferentiality" in countries' trade decisions. Preferentiality here is defined as the tendency to concentrate trade on one or few partners. With this purpose, we adopt a systemic approach through the use of the tools of complex network analysis. In particular, we apply a pattern detection
approach based on community and pseudocommunity analysis, in order to highlight the groups of countries within which most of members' trade occur. The method is applied to two intra-industry trade networks consisting of 221 countries, relative to the low-tech "Textiles and Textile Articles" and the high-tech "Electronics" sectors for the year 2006, to look at the structure of world trade before the start of the international financial crisis. It turns out that the two networks display some similarities and some differences in preferential trade patterns: they both include few significant communities that define narrow sets of countries trading with each other as preferential destinations markets or supply sources, and they are characterized by the presence of similar hierarchical structures, led by the largest economies. But there are also distinctive features due to the characteristics of the industries examined, in which the organization of production and the destination markets are different. Overall, the extent of preferentiality and partner selection at the sector level confirm the relevance of international trade costs still today, inducing countries to seek the highest efficiency in their trade patterns.
C. Piccardi, A. Colombo, and R. Casagrandi,
Connectivity interplays with age in shaping contagion over networks with vital dynamics,
Physical Review E, 91(2), 022809, 2015. [doi]

The effects of network topology on the emergence and persistence of infectious diseases have been broadly explored in recent years. However, the influence of the vital dynamics of the hosts (i.e., birth-death processes) on the network structure, and their effects on the pattern of epidemics, have received less attention in the scientific community. Here, we study Susceptible-Infected-Recovered(-Susceptible) [SIR(S)] contact processes in standard networks (of Erdos-Renyi and Barabasi-Albert type) that are subject to host demography. Accounting for the vital dynamics of hosts is far from trivial, and it causes the scale-free networks to lose their characteristic fat-tailed degree distribution.We introduce a broad class of models that integrate the birth and death of individuals (nodes)
with the simplest mechanisms of infection and recovery, thus generating age-degree structured networks of hosts that interact in a complex manner. In our models, the epidemiological state of each individualmay depend both on the number of contacts (which changes through time because of the birth-death process) and on its age, paving the way for a possible age-dependent description of contagion and recovery processes.We study how the proportion of infected individuals scales with the number of contacts among them. Rather unexpectedly, we discover that the result of highly connected individuals at the highest risk of infection is not as general as commonly believed. In infections that confer permanent immunity to individuals of vital populations (SIR processes), the nodes that
are most likely to be infected are those with intermediate degrees. Our age-degree structured models allow such findings to be deeply analyzed and interpreted, and they may aid in the development of effective prevention policies.


   [cv]

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.