Teaching/Educational Activities
2021
24 Feb  24 May 2021
Dept. of Mathematics, University of Trento, Italy
Course:
Network Science: Theory and Lab
English [
Web]
Metabolic interactions within the cell, the human brain, largescale social and financial systems: what do they have in common? They are complex systems with a nontrivial structure and emergent dynamical properties, from collective phenomena to phase transitions.
The course aims at providing a basic introduction to modeling and analysis of complex networks, from the perspective of the physics of complex systems. The student will acquire new competences in the emergent field of Network Science, such as i) the development of generative models for disordered systems; ii) the analysis of topological properties influencing their transport dynamics (from random walks to synchronization of oscillators, to diffusion of pathogens or information in populations with heterogeneous connectivity); iii) the analysis of critical properties of interconnected systems; iv) the analysis of systems of systems, better known as multilayer networks.
The course consists of lectures on theoretical aspects and a laboratory on computational aspects. It will be jointly followed by MSc students in Data Science and Physics.
2020
24 Feb  24 May 2020
Dept. of Mathematics, University of Trento, Italy
Course:
Network Science: Theory and Lab
English [
Web]
Metabolic interactions within the cell, the human brain, largescale social and financial systems: what do they have in common? They are complex systems with a nontrivial structure and emergent dynamical properties, from collective phenomena to phase transitions.
The course aims at providing a basic introduction to modeling and analysis of complex networks, from the perspective of the physics of complex systems. The student will acquire new competences in the emergent field of Network Science, such as i) the development of generative models for disordered systems; ii) the analysis of topological properties influencing their transport dynamics (from random walks to synchronization of oscillators, to diffusion of pathogens or information in populations with heterogeneous connectivity); iii) the analysis of critical properties of interconnected systems; iv) the analysis of systems of systems, better known as multilayer networks.
The course consists of lectures on theoretical aspects and a laboratory on computational aspects. It will be jointly followed by MSc students in Data Science and Physics.
2019
Mediterranean School of Complex Networks 

31 August6 September 2019
International Summer School, by Manlio De Domenico
English [
Web]
This course is thought as a first introduction to the framework of multilayer networks, i.e. graphs whose nodes are connected by links of different nature. The course will start with a detailed introduction of the multilayer framework, both from the theoretical and the applicative points of view, using the tensorial approach. In particular, it will be shown how to transfer all key concepts of graph theory into the multilayer networks, approaching some also some very recent results in the field. A number of applications to several scientific and socioeconomic scenarios will conclude the theoretical course. Finally, a handson tutorial will allow the student to reach a working knowledge of all the material.
2018
MSc in Statistical Physics 

14 September  20 December 2018
Dept. of Physics, University of Trento, Italy
Course:
Structure and Dynamics of Complex Networks
English [
Web]
Metabolic interactions within the cell, the human brain, largescale social and financial systems: what do they have in common? They are complex systems with a nontrivial structure and emergent dynamical properties, from collective phenomena to phase transitions.
The course aims at providing a basic introduction to modeling and analysis of complex networks, from the perspective of the physics of complex systems. The student will acquire new competences in the emergent field of Network Science, such as i) the development of generative models for disordered systems; ii) the analysis of topological properties influencing their transport dynamics (from random walks to synchronization of oscillators, to diffusion of pathogens or information in populations with heterogeneous connectivity); iii) the analysis of critical properties of interconnected systems; iv) the analysis of systems of systems, better known as multilayer networks.
Mediterranean School of Complex Networks 

18 September 2018
International Summer School, by Manlio De Domenico
English [
Web]
This course is thought as a first introduction to the framework of multilayer networks, i.e. graphs whose nodes are connected by links of different nature. The course will start with a detailed introduction of the multilayer framework, both from the theoretical and the applicative points of view, using the tensorial approach. In particular, it will be shown how to transfer all key concepts of graph theory into the multilayer networks, approaching some also some very recent results in the field. A number of applications to several scientific and socioeconomic scenarios will conclude the theoretical course. Finally, a handson tutorial will allow the student to reach a working knowledge of all the material.
2125 May 2018
University of Trento, Italy
Course for the ICT Doctoral School, by Manlio De Domenico
English [
Web]
This course is thought as a first introduction to the framework of multilayer networks, i.e. graphs whose nodes are connected by links of different nature. The course will start with a detailed introduction of the multilayer framework, both from the theoretical and the applicative points of view, using the tensorial approach. In particular, it will be shown how to transfer all key concepts of graph theory into the multilayer networks, approaching some also some very recent results in the field. A number of applications to several scientific and socioeconomic scenarios will conclude the theoretical course. Finally, a handson tutorial will allow the student to reach a working knowledge of all the material.
Program:
 Lecture 1: From Classical to Multilayer Networks (classification; mathematical formulation)
 Lecture 2: Dynamics in Multilayer Networks (spreading; robustness to attacks)
 Lecture 3: Multilayer Mesoscale Organization
 Lecture 4: Multilayer Descriptors
 Lecture 5: Timevarying Networks