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Title of the thesis: Multilayer networks: phenomena, theory, and practice

Thesis defender: Tarmo Nurmi
Opponent: Professor NataÅ¡a Pržulj, Mohamed bin Zayed University of Artificial Intelligence, United Arab Emirates & University College London, United Kingdom
Custos: Professor Mikko Kivelä, Aalto University School of Science

Networks are an excellent tool for modeling certain types of complex systems. Often, networks are
represented with graphs, a powerful but simple abstraction that has been very successful in the
analysis of networks. However, graphs sometimes fail to capture essential aspects of the underlying
network phenomenon by being too simplistic. Many real-world network phenomena involve multiple
types of interactions, feature interdependencies, include hierarchies or different scales, change in
time, or otherwise exhibit a multilevel or layered nature. Many of these phenomena can be modeled
with multilayer networks, a relatively recent extension of the graph abstraction that has proven
effective in capturing the nature of multilayered phenomena.

The thesis presents an in-depth exploration of some of the core aspects that define multilayer network
science and illuminates the critical considerations that are essential for research into fundamentally
multilayered phenomena. The primary focus areas are the phenomena to which multilayer networks
bring a new and better understanding, the development of the foundational mathematical theory
behind multilayer networks, the creation of multilayer-centered algorithms, and the development of
practical tools for multilayer network analysis.

Keywords: Complex networks, multilayer networks, network analysis 

Contact information: tarmo.nurmi@aalto.fi 

Thesis available for public display 10 days prior to the defence at .