Quantitative Network Science

Quantitative network science, the science of studying and analysing complex networks, has become increasingly important and has grown significantly in recent years. Network science and network data analysis are not confined to any single scientific discipline as networks occur in diverse areas of science.

Networks provide an abstract way of describing relationships and interactions between elements of complex and heterogeneous systems. For example, the World Wide Web can be represented as a network whose vertices are the HTML documents, connected by the hyperlinks that point from one page to another. On a different level, our nervous system forms a large network, whose vertices are the neurons and nerve cells, which are connected by axons. Complex networks are also considered in social and economic sciences. There the vertices represent (specific groups of) individuals or entities, and the edges describe social (or some other type of) interaction between them. Yet another example of the use of networks is in information visualization and visual analytics in order to discover unexpected patterns in network data.

While the scientific disciplines in which networks occur are diverse, the needs for analysis are similar and may be dealt with by using the same or similar quantitative methods and models. These include methods and theories ranging from mathematical graph theory and statistical network models to visualization techniques in computer science. The Research Focus Quantitative Network Science intends to bundle the different activities within network science at the LMU Munich and brings together mathematicians, statisticians, and computer scientists with empirical scientists from a wide range of disciplines in order to advance the field of quantitative network science.


Working Group

  • Prof. Dr. Andreas Butz
    (Institute for Informatics, Human-Computer-Interaction, LMU)
  • Prof. Dr. Göran Kauermann
    (Department of Statistics, Statistics and its Applications in Economics and Social Sciences, LMU)
  • Prof. Dr. Martin Kocher
    (Department of Economics, Behavioral Economics and Experimental Economics, LMU)
  • Dr. Jacek Puchalka †
    (Gene Center, LMU)
  • Prof. Dr. Hinrich Schütze
    (Center for Information and Language Processing, Computational Linguistics, LMU)
  • Prof. Dr. Gregory Wheeler
    (Munich Center for Mathematical Philosophy, Philosophy of Science, LMU)
  • Prof. Dr. Ralf Zimmer
    (Teaching and Research Unit Bioinformatics, LMU)

Advisory Board

  • Prof. Dr. Ulrike Gaul
    (Gene Center, LMU)
  • Prof. Dr. Sonja Greven
    (Department of Statistics, Biostatistics, LMU)
  • Dr. Alex Loebel
    (Department of Neurobiology, Computational Neuroscience, LMU)
  • Prof. Dr. Thilo Meyer-Brandis
    (Department of Mathematics, Financial Mathematics, LMU)
  • Prof. Dr. Konstantinos Panagiotou
    (Department of Mathematics, Discrete and Algorithmic Mathematics, LMU)
  • Prof. Dr. Paul W. Thurner
    (Geschwister Scholl Institute of Political Science, Empirical Political Research and Policy Analysis, LMU)
  • Prof. Dr. Martin Wirsing
    (Teaching and Research Unit Programming and Software Engineering, LMU)


  • Dr. Constanze Schmaling
    (Department of Mathematics, Financial Mathematics, LMU)

Visiting Fellows

Prof. Yan Chen, Ph.D.

Previous Visiting Fellow

Prof. Dr. Ulrik Brandes

Previous Visiting Fellow

Prof. Marco Maggis, Ph.D.

Previous Visiting Fellow


  • Workshop with Evening Lecture by Prof. Dr. Paul Embrechts – "Computational Methods for Networks"
    (Winter Semester 2015/16)
  • Lecture by Prof. Dr. Alexander Borst and Dr. Moritz Helmstädter – "How Do Neuronal Circuits Operate?"
    (Winter Semester 2015/16)
  • International Workshop with Evening Lecture by Prof. Dr. Stefan Thurner – "What’s new in networks? – Building bridges between computational, mathematical and statistical network analysis"
    (Summer Semester 2016)
  • Lecture by Dr. Achim Edelmann und Prof. Kieran Healy, Ph.D. – "Using Computational Tools to Uncover Structure and Status in Academic Fields and Public Debates"
    (Summer Semester 2017)


  • Quantitative Network Science (QNetS), in: CAS Concepts 5 (2017).

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