Patterns
that Matter

News and updates

  • 14.03.2022 Our paper titled Robust Subgroup Discovery, with Hugo Proença, Peter Grünwald, and Thomas Bäck, got accepted for publication in Data Mining and Knowledge Discovery. Congratulations Hugo!
  • 03.02.2022 Our paper titled Associations between symptoms, donor characteristics and IgG antibody response in 2082 COVID-19 convalescent plasma donors, with Marieke Vinkenoog et al. got accepted for publication in Frontiers in Immunology. Congratulations Marieke!
  • 27.01.2022 I received the Senior Teaching Qualification (SKO) certificate! Read the news article.
  • 20.01.2022 Our paper titled Finding Efficient Trade-offs in Multi-Fidelity Response Surface Modeling, with Sander van Rijn, Sebastian Schmitt, and Thomas Bäck got accepted for publication in Engineering Optimization. Congratulations Sander!
  • 16.10.2021 Hugo Manuel Proença has successfully defended his PhD thesis titled Robust rules for prediction and description. Congratulations Dr. Hugo Proença!
  • 14.06.2021 Sarang Kapoor has successfully defended his PhD thesis titled Subjectively Interesting Patterns in Networks. Congratulations Dr. Sarang Kapoor!
  • 22.12.2020 Our paper titled Estimating Conditional Mutual Information for Discrete-Continuous Mixtures using Multi-Dimensional Adaptive Histograms, with Alexander Marx and Lincen Yang, got accepted at SDM 2021. Congratulations Alex and Lincen!
  • 02.12.2020 Our paper titled Evaluating privacy of individuals in medical data, with Shannon Kroes, Mart Janssen, and Rolf Groenwold, got accepted for publication in Health Informatics Journal. Congratulations Shannon!
  • 14.09.2020 I received a Journal Track Reviewer Award at ECML PKDD 2020.
  • 17.08.2020 Our paper titled Online Summarization of Dynamic Graphs using Subjective Interestingness for Sequential Data, with Sarang Kapoor and Dhish Saxena, got accepted for publication in the ECMLPKDD journal track of Data Mining and Knowledge Discovery. Congratulations Sarang!
  • 24.07.2020 Our paper titled Social Fluidity in Children's Face-to-Face Interaction Networks, with Daniela Gawehns, got accepted at GEM 2020. Congratulations Daniela!
  • 05.06.2020 Our paper titled Discovering Outstanding Subgroup Lists for Numeric Targets using MDL, with Hugo Proença, Peter Grünwald, and Thomas Bäck, got accepted at ECML PKDD 2020. Congratulations Hugo!
  • 23.04.2020 Our paper titled First results of a ferritin-based blood donor deferral policy in the Netherlands, with Marieke Vinkenoog, Katja van den Hurk, Marian van Kraaij, and Mart Janssen, got accepted for publication in Transfusion. Congratulations Marieke!

I am associate professor and group leader of the Explanatory Data Analysis group at the Leiden Institute of Advanced Computer Science (LIACS), the computer science institute of Leiden University. My primary research interest is exploratory data mining: how can we enable domain experts to explore and analyse their data, to discover structure and—ultimately—novel knowledge?

For this it is important that methods and results are explainable to domain experts, who may not be data scientists. My signature approach is to define and identify patterns that matter, i.e., succinct descriptions that characterise relevant structure present 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. Information theoretic concepts such as the Minimum Description Length (MDL) principle have proven very useful to this end. I am also interested in interactive data mining, i.e., involving humans in the loop. Finally, I am interested in fundamental data mining research for real-world applications, both in science (e.g., life sciences, social sciences) and industry (e.g., manufacturing and engineering, aviation), as this is the best way to show that the theory works in practice.

I am affiliated with SAILS and DSRP, the university-wide research programmes for artificial intelligence and data science, respectively. Broadly speaking, my research can be situated in the fields of data mining, machine learning, data science, and artificial intelligence (AI).

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Activities

Current and upcoming Recent

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Selected recent publications

In press
Proença, HM, Grünwald, P, Bäck, T & van Leeuwen, M Robust subgroup discovery. Data Mining and Knowledge Discoveryimplementation
2022
van Rijn, S, Schmitt, S, van Leeuwen, M & Bäck, T Finding Efficient Trade-offs in Multi-Fidelity Response Surface Modeling. Engineering Optimization
website
Yang, L & van Leeuwen, M Probabilistic Rule Sets Ready for Interactive Machine Learning. In: AAAI'22-Workshop on Interactive Machine Learning, 2022.
Vinkenoog, M, Steenhuis, M, ten Brinke, A, van Hasselt, C, Janssen, M, van Leeuwen, M, Swaneveld, F, Vrielink, H, van de Watering, L, Quee, F, van cen Hurk, K, Rispens, T, Hogema, B & van der Schoot, E Associations between symptoms, donor characteristics and IgG antibody response in 2082 COVID-19 convalescent plasma donors. Frontiers in Immunology, Frontiers
2021
Kroes, SKS, Janssen, MP, Groenwold, RHH & van Leeuwen, M Evaluating privacy of individuals in medical data. Health Informatics Journal, SAGE Publications
Marx, A, Yang, L & van Leeuwen, M Estimating Conditional Mutual Information for Discrete-Continuous Mixtures using Multi-Dimensional Adaptive Histograms. In: Proceedings of the SIAM Conference on Data Mining 2021 (SDM'21), SIAM, 2021.
website
Kapoor, S, Saxena, DK & van Leeuwen, M Online Summarization of Dynamic Graphs using Subjective Interestingness for Sequential Data. Data Mining and Knowledge Discovery vol.35(1), pp 88-126, 2021. (ECML PKDD journal track)
implementation