- The Python Ecosystem for Data Science: A Guided Tour at PyData Warsaw 2017
- a talk introducing the NetworKit software package
- a popular science introduction to social network analysis (in German, hosted by netzstrategen)
- The Python Ecosystem for Data Science: A Guided Tour, PyData Warsaw, October 2017
- paper presentation at Complex Networks conference, Milano, 2016
- PhD thesis defense at Karlsruhe Institute of Technology, 2016
- guest talk at Clemson University, 2015
Refer to my GitHub page for current open-source contributions.
Throughout my studies and PhD work I have developed scientific software with a focus on graph algorithms. I have initiated the open-source project NetworKit which provides a collection of tools for data analysis of large complex networks, implemented in C++, Python and Cython. From 2012 – 2016 I contributed as maintainer, software architect and algorithm developer.
I have published work on graph algorithms for complex network analysis, which has earned me a PhD in computer science from the Karlsruhe Institute of Technology with the thesis Algorithms and Software for the Analysis of Large Complex Networks – and an Erdös-Number of 3. DBLP has a full list of my publications, including
- Christian L. Staudt, Henning Meyerhenke: Engineering Parallel Algorithms for Community Detection in Massive Networks. IEEE Trans. Parallel Distrib. Syst. 27(1): 171-184 (2016)
- Michael Hamann, Gerd Lindner, Henning Meyerhenke, Christian L. Staudt, Dorothea Wagner:
Structure-preserving sparsification methods for social networks. Social Netw. Analys. Mining 6(1): 22:1-22:22 (2016)
- Christian L. Staudt, Aleksejs Sazonovs, Henning Meyerhenke: NetworKit: A Tool Suite for Large-scale Complex Network Analysis. Network Science.