Main research interest
The Probability Group (Van der Hofstad) investigates complex network data andrandom graph models for them, as well as network functionality. A key problem is to entangle the relationship between the topology of the networkinvolved and the behavior of processes on them. Particular research themes are the dynamics on and of networks, with the aim to predict their evolution on the basis of data. We apply our methodology to various real-world networks, such as citation and social networks, and the brain.
We collaborate with the Stochastic Operations Research group (Van Leeuwaarden) on analyzing the community structure of complex networks, and with the Statistics Group (Castro) on community detection.
In collaboration with Prof. Bert Meijer and his team, we use super-resolution microscopy data to find that exchange patterns of one-dimensional aggregates are rather different than expected.
- L. Albertazzi et al. Probing exchange pathways in one-dimensional aggregates with super-resolution microscopy. Science 344(6183): 491-495, (2014).
Jointly with Ludo Waltman at CWTS Leiden, PhD student Alessandro Garavaglia uses Web of Science data to analyze citation patterns in networks of scientific papers, so as to quantify the citation evolution of papers in various disciplines, so as to predict success early on.
- VICI program `Random networks: universality in structure and function’Discovering the universal aspects of complex network evolution and functionality.
- NETWORKS Gravitation program Bringing together stochastics and algorithmics to model, understand, control and optimize large-scale networks, with applications to traffic, communication, healthcare, service engineering and energy networks.
- VENI program `Explosive propagation and community formation on networks’How does information spread in highly heterogeneous networks containing highly connected nodes?