Patterns
that Matter

News and updates

  • 07.11.2019 NWO has awarded a TTW Perspectief grant to our 5.7M€ research programme titled Integration of Data-drIven and model-based enGIneering in fuTure industriAL Technology With value chaIn optimizatioN (DIGITAL TWIN).
  • 25.10.2019 Our paper titled Interpretable multiclass classification by MDL-based rule lists, with Hugo Proença, got accepted for publication in Information Sciences. Congratulations Hugo!
  • 01.09.2019 As of today I am programme manager of Leiden University's master's programme in Computer Science.
  • 19.07.2019 Our paper titled Challenges and Limitations in Clustering Blood Donor Hemoglobin Trajectories, with Marieke Vinkenoog and Mart Janssen, got accepted at AALTD 2019. Congratulations Marieke!
  • 22.02.2019 I obtained the BKO, i.e., the University Teaching Qualification for Dutch universities (in Dutch: Basiskwalificatie Onderwijs).
  • 18.01.2019 NWO has awarded me a TOP grant (module 2) for my research proposal titled Human-Guided Data Science by Interactive Model Selection. Read the news article.
  • 01.09.2018 Our paper titled Identifying flight delay patterns using diverse subgroup discovery, with Hugo Proença, Ruben Klijn, and Thomas Bäck, got accepted at SSCI 2018. Congratulations Hugo!
  • 30.08.2018 Our paper titled Predicting outcome of endovascular treatment for acute ischemic stroke: potential value of machine learning algorithms, with Hine van Os and colleagues, got accepted at Frontiers of Neurology. Congratulations Hine!
  • 01.08.2018 I am now general chair of the IDA Council, the steering committee of the IDA symposium series. First up: IDA 2018 in Den Bosch, October 24-26!
  • 01.05.2018 Our research proposal titled Data Science for State-of-the-Art Blood Banking (BloodStarT), with Mart Janssen, Aske Plaat, Marian van Kraaij, and Katja van den Hurk, was granted by Sanquin.
  • 24.03.2018 Our paper titled Multi-Fidelity Surrogate Model Approach to Optimization, with Sander van Rijn, Sebastian Schmitt, Markus Olhofer, and Thomas Bäck, got accepted at GECCO 2018. Congratulations Sander!
  • 01.02.2018 Our special issue on Interactive Data Exploration and Analytics (IDEA), co-edited with Polo Chau, Jilles Vreeken, Dafna Shahaf, and Christos Faloutsos, was published in TKDD.

I am assistant 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 the Leiden Centre of Data Science (LCDS) and university-wide Data Science Research Programme (DSRP). 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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Selected recent publications

2020
Proença, HM & van Leeuwen, M Interpretable multiclass classification by MDL-based rule lists. Information Sciences vol.512, pp 1372-1393, Elsevier, 2020.implementationwebsite
2019
Vinkenoog, M, Janssen, M & van Leeuwen, M Challenges and Limitations in Clustering Blood Donor Hemoglobin Trajectories. In: 4th Workshop on Advanced Analytics and Learning on Temporal Data at ECMLPKDD 2019, 2019.
Gawehns, D, Veiga, G & van Leeuwen, M Focus on dynamics: a proof of principle in exploratory data mining of face-to-face interactions. In: Proceedings of the 5th International Conference on Computational Social Science (IC2S2), 2019. (Poster presentation)
van Leeuwen, M, Chau, DH, Vreeken, J, Shahaf, D & Faloutsos, C Addendum to the Special Issue on Interactive Data Exploration and Analytics (TKDD, Vol. 12, Iss. 1): Introduction by the Guest Editors. Transactions on Knowledge Discovery from Data vol.13(1), ACM, 2019.
2018
Proença, HM, Klijn, R, Bäck, T & van Leeuwen, M Identifying flight delay patterns using diverse subgroup discovery. In: Proceedings of the Symposium Series on Computational Intelligence (SSCI'18), IEEE, 2018.
van Rijn, S, van Leeuwen, M, Schmitt, S, Olhofer, M & Bäck, T Multi-Fidelity Surrogate Model Approach to Optimization. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'18), ACM, 2018.
van Os, H, Ramos, L, Hilbert, A, van Leeuwen, M, van Walderveen, M, Kruyt, N, Dippel, D, Steyerberg, E, van der Schaaf, I, Lingsma, H, Schonewille, W, Majoie, C, Olabarriaga, S, Zwinderman, K, Venema, E, Marquering, H & Wermer, M Predicting outcome of endovascular treatment for acute ischemic stroke: potential value of machine learning algorithms. Frontiers in Neurology vol.9(784), Frontiers, 2018.
van Leeuwen, M, Chau, DH, Vreeken, J, Shahaf, D & Faloutsos, C Editorial: TKDD Special Issue on Interactive Data Exploration and Analytics. Transactions on Knowledge Discovery from Data vol.12(1), ACM, 2018.