Robbert van der Burg, MSc

Robbert is a PhD candidate at the Department of Mathematics of the Faculty of Science at the Vrije Universiteit Amsterdam. He started his doctoral research in October 2025. In addition to his research activities, he is affiliated with the department as a Teaching Assistant for numerous courses.

He obtained a Bachelor’s degree in Mathematics from Leiden University, followed by a Master’s degree in Econometrics and Operations Research from the Vrije Universiteit Amsterdam, with a specialization in Operations Research Theory. During his studies, he developed a strong interest in probabilistic modeling, stochastic processes, and the mathematical analysis of networked systems.

His doctoral research is conducted under the supervision of dr. Alessandro Zocca and prof. dr. Frank van der Meulen, and is embedded in a research project funded through a competitive research grant. His academic interests lie at the intersection of probability theory, network science, and stochastic modeling, with a particular emphasis on understanding rare but high-impact events in spatially distributed systems.

His PhD research focuses on probabilistic modeling of weather-driven failures in critical infrastructure networks, such as power grids. These networks are inherently spatially distributed, and when subjected to extreme environmental stressors, such as wind storms, floods, or heatwaves, failures rarely occur in isolation. Instead, extreme weather manifests as a spatial field with a characteristic footprint, simultaneously affecting multiple components of the network. As a result, the vulnerability of nodes is strongly shaped by spatial dependence and correlation structures.

In addition to his main PhD topic, he maintains a strong interest in Markov chain theory and network analysis. Related side projects include the study of hitting times on graph models, first passage times, and the Kemeny constant, as well as applications of these concepts in social network analysis. Together, these research directions contribute to a broader understanding of dynamics, risk, and resilience in complex networked systems.

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