I am an assistant professor at Twente Universty. I work at the intersection of probability theory, graph theory and stochastic networks. Problems I investigate are inspired by applications in network science, physics and computer science. Some of my research interests are:
Epidemic and percolation processes on networks have many applications, ranging from virus spreading to internet outages. I am interested in analyzing epidemic or percolation processes on random graph models: null models for real-world networks.
Patterns in networks
Small subgraphs that occur frequently in a network data set can reveal interesting properties of the underlying data. I am interested in the occurrence of these small subgraphs in random graph models. How frequently do subgraphs appear in random graph models? And where in the graph can they be found?
In most networks, we can interpret the vertices as lying in a geometric space. For example, internet users may have a two-dimensional position. In social media networks, you can interpret the position of a person as their interests, location and so on. I am interested in investigating such geometric networks from a mathematical point of view.
What attracted me to my new department and university?
I like the fact that our group combines interesting mathematical research with real-world applications of mathematics.
What are my one or two most favorite projects at this moment?
I am currently investigating how we can detect the presence of `features' of network members from the network connections only.
What are my fondest hopes for my research and my teaching for the next few years?
I would like to be able to gain more understanding of realistic, mathematical network models that can be applied to social media, chemical reactions, the internet and many more.
In teaching, I hope to show students that mathematics is beautiful and intuitive, even though you sometimes have to work hard to understand it.
What I'd like to explore, learn or do with other scientists?
I would like to connect to scientists from all kinds of areas where networks are used, to learn about their specific properties, and interesting mathematical problems that can arise there.