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.

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