I am assistant professor and group leader of the Explanatory Data Analysis group at the Leiden Institute of Advanced Computer Science (LIACS). LIACS is the computer science institute of Leiden University, where I also participate in the Leiden Data Science research programme. My main interest is exploratory data mining: how can we enable domain experts to explore and analyse their data, to discover structure that lead to novel knowledge?
For this it is very important that all methods and results are explainable to domain experts, who may not be data scientists. The approach I take is to define and identify patterns that matter, i.e., succinct descriptions that characterise relevant structure in the data. Which patterns matter strongly depends on the data and task at hand, hence defining the problem is one of the key challenges of exploratory data mining. I often use patternbased modelling techniques, for which information theoretic concepts such as the Minimum Description Length (MDL) principle have proven very useful. I am also interested in interactive data mining, i.e., involving humans in the loop.
Finally, I find it very interesting to do fundamental data mining for realworld applications, both in science (e.g., life sciences, social sciences) and industry (e.g., manufacturing and engineering, aviation). There is no better way to show the potential of exploratory data mining than by demonstrating that patterns matter.
2017 

Explaining Deviating Subsets through Explanation Networks. In: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD'17), Springer, 2017. 

Learning what matters – Sampling interesting patterns. In: Proceedings of the PacificAsia Conference on Knowledge Discovery and Data Mining (PAKDD'17), pp 534546, Springer, 2017. 

Relational Data Factorization. Machine Learning vol.106(12), pp 18671904, Springer, 2017. 

Flexible constrained sampling with guarantees for pattern mining. Data Mining and Knowledge Discovery vol.31(5), pp 12661293, Springer, 2017. (ECMLPKDD'17 Special Issue) 

Semiring Rank Matrix Factorisation. Transactions on Knowledge and Data Engineering vol.29(8), pp 17371750, IEEE, 2017. 

2016 

Towards Data Driven Process Control in Manufacturing Car Body Parts. In: Proceedings of IEEE International Conference on Computational Science and Computational Intelligence (IEEE CSCIISBD'16), IEEE, 2016. 

Evolving the Structure of Evolution Strategies. In: Proceedings of IEEE Symposium Series on Computational Intelligence (IEEE SSCI'16), IEEE, 2016. 

Local SubspaceBased Outlier Detection using Global Neighbourhoods. In: Proceedings of IEEE International Conference on Big Data (IEEE BigData'16), IEEE, 2016. 

Expect the Unexpected  On the Significance of Subgroups. In: Proceedings of Discovery Science (DS'16), pp 5166, Springer, 2016. 

Simultaneous discovery of cancer subtypes and subtype features by molecular data integration. Bioinformatics vol.32(17), pp 445454, Oxford University Press, 2016. 

A KNIMEbased Analysis of the Zebrafish Photomotor Response Clusters the Phenotypes of 14 Classes of Neuroactive Molecules. Journal of Biomolecular Screening vol.21(5), pp 427436, SAGE Publishing, 2016. 

Subjective Interestingness of Subgraph Patterns. Machine Learning vol.105(1), pp 4175, Springer, 2016. 

2015 

An exercise in declarative modeling for relational query mining. In: Proceedings of the 25th International Conference On Inductive Logic Programming (ILP'15), pp 166182, Springer, 2015. 

Rank Matrix Factorisation. In: Proceedings of the 19th PacificAsia Conference on Knowledge Discovery and Data Mining (PAKDD'15), pp 734746, Springer, 2015. 

Same bang, fewer bucks: efficient discovery of the costinfluence skyline. In: Proceedings of the SIAM Conference on Data Mining 2015 (SDM'15), SIAM, 2015. 

VIPER  Visual Pattern Explorer. Demo paper in: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD'15), Springer, 2015. 

Association Discovery in TwoView Data. Transactions on Knowledge and Data Engineering vol.27(12), pp 31903202, IEEE, 2015. 