The final annual meeting took place on 9th and 10th July 2022 in Frankfurt and was collocated with the 82. GI Workshop on Algorithms and Complexity (Theorietag).

NetworKit is an open open-source toolkit of algorithms for large-scale network analysis. The upcoming NetworKit Day 2020 is a meeting of the NetworKit community and will be held online via Zoom.

The event intends to present NetworKit to people who don't know it yet, to update more seasoned users and developers and to discuss future development directions including feedback on the current status. Also, two invited scientific talks by Jörn Kreutel from Beuth Hochschule für Technik Berlin and by Mattia D'Emidio from University of L'Aquila are featured.



October 15th, 2020

Registration deadline is October 13th, 2020



Further information and registration can be found here.



The Indo-German Spring School will take place at IIIT Delhi, India.


February 10 ‒ 13, 2020

More details can be found here.


Peter Sanders receives an European Reasearch Council's Advanced Grant for his project "ScAlBox – Engineering Scalable Algorithms for the Basic Toolbox". The ERC selects and funds the very best, creative researchers once a year to run projects based in Europe. In his project "ScAlBox" the computer scientist Peter Sanders develops basic computing tools for many different applications at the Karlsruhe Institute of Technology Department of Informatics. The project's goal is to provide algorithms and software libraries that can handle very large amounts of data and can be executed on millions of processors working in parallel.


During the first week of September 2019 SPP members Timo Bingmann (KIT), Ulrich Meyer (Goethe University), and Matthias Mnich (Bonn University) together with Tim Conrad (FU Berlin) co-organised a GI-Dagstuhl seminar with close to thirty participants.
The workshop targeted algorithms and systems for big data, with the objective to discuss and identify current research challenges and prospective solutions in the areas of big data management, algorithmic research, machine learning, distributed systems, and applications. More pieces of information can be found here.


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