For his project, Boxma wants to combine two seemingly very different areas from the applied probability theory: the queuing theory and insurance mathematics. Situations involving a single queue have been studied in-depth many times before, but reality (including the Internet) often deals with whole networks of queues. The capital of reinsurers is often interwoven through reinsurance contracts quite intricately as well. Still, realizing these more ‘high-dimensional’ models to describe these more realistic systems is tough. Boxma has therefore decided that he wants to use his TOP Grant to develop mathematical tools to improve the study into two-dimensional stochastic processes.

Van der Aalst’s project will be carried out at the new Data Science Center Eindhoven (DSC/e), and the process mining expert will be in charge. The project, which has been named Desire Lines in Big Data, aims at scanning the digital records of data systems in hospitals, for example, in search of so-called desire lines: ways in which people circumvent official procedures. Such information is valuable, because it could lead to more efficient procedures. Van der Aalst will be focusing on data sets that are too large to analyze using conventional methods.