Duration: 01.01.2013-31.12.2016; extension 01.01.2017-31.12.2022; extension 01.01.2023-31.12.2028

Co-funded by: ARIS

Project coordinator: Laboratory for Complex Systems and Data Science

Type of project: Research and development project

Role of FIŠ: Applicant

Complex network science studies the mechanisms of collective phenomena that arise through self-organisation in systems composed of many interconnected entities, such as genes, ants or persons. By combining graph theory and experimental insight into real complex systems such as society or the Internet, this young interdisciplinary science contributes fundamental results for improving infrastructure networks based on an understanding of genetic systems.

The research work of the Complex Networks programme is thematically divided into two main work streams. Theoretical Network Science and Data Science and Real Networks, each of which is further divided into three strands due to the broad and highly interdisciplinary composition of the programme group. This is also reflected in the publications, as the group’s research has been published in scientific journals ranging from mathematics and theoretical computer science, to chemistry and biology, from the technical sciences to the social sciences and bibliographic sciences.

The first work stream focuses more on basic research, mainly carried out by members of the programme team with a background in the life sciences. The work stream consists of the following three thematic strands:

  • Network modelling and simulation
  • Optimisation problems in graphs
  • Graph measures.

The second work strand focuses on the study of real networks, or the modelling of networks based on real data. This strand is also divided into three thematic branches:

  • Computational Social Science
  • Networks in biomedicine
  • Alternative Directions in Network Science.

Research programme leader: Prof. Dr. Riste Škrekovski

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