In this blog, we - the research group *Modeling and Analysis of Complex Systems* (MACSy) - present some of our research results.

The group is headed by Prof. Dr. Henning Meyerhenke and works on scalable algorithms for large and complex networked systems. We employ the algorithm engineering cycle of modeling, design, analysis, implementation, and experimental evaluation in order to obtain practical solution methods with sound theoretical foundations for real-world problems.

Our current focus areas are:

  • Algorithmic analysis of large complex networks, in particular for dynamic scenarios
  • Combinatorial scientific computing, in particular load balancing and scheduling
  • Applied optimization, in particular for complex algorithmic problems in the natural sciences


Jul 12, 2021: Next paper online

"Improving the Betweenness Centrality of a Node by Adding Links" (authors: E. Bergamini, P. Crescenzi, G. D'angelo, H. Meyerhenke, L. Severini, Y. Velaj) is the next paper which was published online on our Research Blog. It was originally published in JEA 2018.

Besides an overview over the experiments and outcomes of the paper, we also put the numerical data and Jupyter-notebooks in the Downloads-section. This enables to recreate the original plots and screenshots. Additionally scripts and graph-data is also available for download. All scripts and functions were ported to be compatible with the most recent release of NetworKit (currently: v9.0).

Nov 17, 2020: First paper integrated

"Approximation of the Diagonal of a Laplacian's Pseudoinverse for Complex Network Analysis" (authors: Angriman, Predari, van der Grinten, Meyerhenke) is the first paper which appears on our Research Blog. Checkout our subpage with all details about key outcomes, experimental data and downloads. The paper was originally accepted by ESA 2020.

Nov 16, 2020: Website released

We are pleased to present this new blog website. In the future, we (the MACSy research group) present some of our research here to provide additional information on data, codes, and experimental results.