• Home
  • About
  • People
  • Research
  • Partners
  • Contact

Computational Network Science Lab

Network science research lab at Leiden University

  • Home
  • About
  • People
  • Research
  • Partners
  • Contact

Andre Beijen starts as PhD candidate

November 1, 2019 network science

Andre Beijen started his PhD project in the fall of 2019 in the Computational Network Science group at LIACS, Leiden University. Andre has a degree in applied physics from Technical University Delft, where he graduated in statistical signal processing. Since then he worked worked in high tech environments, such as optics, DSP programming and encryption. The last 18 years he worked at KPN, the incumbent telecom provider of the Netherlands, especially in the field of network technology. This includes mobile and fixed access networks, local and wide area networks, core and transport networks and datacenter networks. The last 5 years Andre worked on network function virtualization and software defined networks, which is where he also got the idea for his PhD project. The goal is to study “self learning” or “self optimizing networks”; smart networks that are able to adapt automatically to predicted future network states.

Visit Andre’s university profile page

Efficiently counting complex multilayer temporal motifs in large-scale networks

4th Workshop on Mining Actionable Insights from Social Networks at TheWebConf 2020 in Taiwan

About the CNS Lab

The Leiden Computational Network Science Lab (CNS Lab) is a research group working on methods for knowledge discovery from real-world network data. We develop methods and algorithms to unveil patterns in dynamic complex networks from a range of application domains, including (online) soclal networks, scientific collaboration networks and economic networks. The CNS Lab is lead by Frank Takes and affiliated with the Theory and Data Science clusters of the Department of Computer Science (LIACS) of Leiden University.

Twitter

Tweets by funwithnetworks
Proudly powered by WordPress | Theme: Doo by ThemeVS.