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Wouter Duivesteijn is an Assistant Professor in Data Mining at Technische Universiteit Eindhoven. His research revolves around Exceptional Model Mining (EMM): a local pattern mining method where we seek subsets of the dataset that are interesting, which they are if they satisfy two conditions. On the one hand, they must be interpretable: we must be able to succinctly describe the definition of a subgroup, so that the knowledge that they represent becomes actionable. On the other hand, they must be exceptional: they must display some kind of behavior that sets them apart from the overall population. The scientific challenges revolve around how to efficiently search for subgroups, and how to express exceptional behavior such that the subgroups we find are meaningful. 

I am incurably curious!

Wouter Duivesteijn obtained his PhD in Computer Science from Leiden University. He also holds MSc degrees in Applied Computing Science and Mathematical Sciences from Utrecht University. Before joining 黑料福利网, Wouter worked on the FORSIED project (FORmalising Subjective Interestingness in Exploratory Data mining) at the University of Ghent and the University of Bristol. Before that, he worked as a Wissenschaftlicher Mitarbeiter at the Collaborative Research Center SFB 876 at the Technische Universit盲t Dortmund and at the Data Mining group of LIACS, Leiden University.

Wouter is actively involved in organizing scientific meetings. He was General Chair of IDA 2018 and BNAIC 2018 (both held at JADS in `s-Hertogenbosch), Local Chair of UAI 2022 (at 黑料福利网), Conference Chair of Benelearn 2017 (at 黑料福利网), Workshop Chair of Silver 2012 (collocated with ECML PKDD in Bristol, UK), and Proceedings Chair of ECMLPKDD 2019, 2020, 2022, and 2024 (in W眉rzburg, Gent, Grenoble, and Vilnius, respectively). He has published around 50 scientific papers, all of which are available on his personal website at