Jilles Vreeken
Professor of Computer Science
Saarland University
Im Oberem Werk 1, Room 0.01
66386 St. Ingbert, Germany
vreeken@cispa.de
+49 681 87083 2173
Jilles at work at the airport

I am faculty (W3, tenured) at the CISPA Helmholtz Center for Information Security, where I lead the research group on Exploratory Data Analysis. I'm Honorary Professor of Computer Science at Saarland University and ELLIS Faculty of the Saarbrücken Unit on Artificial Intelligence and Machine Learning.

My research is concerned with causality and unsupervised learning. In particular, I enjoy developing theory and algorithms for answering fundamentally exploratory questions, such as 'what is going on in my data?', 'what causes what and how?', 'what can we learn from this model?' without having to make unnecessary or unjustified assumptions. To identify what is worth knowing, I like to take a principled approach, such as based on information theory, and then proceed to develop efficient algorithms for extracting useful interpretable results. I like all data types equally much.

I am interested in causal inference under realistic conditions, such as e.g. under hidden confounding or selection bias, when the i.i.d. assumption does not hold, or while making use of background knowledge. I am always interested in how to summarize the essence of complex data and models in easily understandable and actionable terms, and using these to obtain better, more robust, and more useful models. I find the combination of these two threads especially exciting.


If you are looking for a bit of procrastination, consider
Research in Progress — the secret life of research, through the medium of animated GIFs.


Activities more ▾

Teaching and Advising more ▾
  • Postdoctoral Researchers
    • Dr. Janis Kalofolias
    • Dr. Lénaïg Cornanguer
  • Doctoral Researchers
  • Research Assistants
    • Dinesh Adithya
    • Tim Bauerschmidt
    • Moritz Ditter
    • Felix Falkenberg
    • Julius Kamp
    • Tim Kruse
    • Ahmed Musa
    • Luis Paulus
    • Benedikt Schardt
    • Aleena Siji
    • Hendrik Suhr
    • Anton Voran
    • Matthias Wilms
  • Former MSc Thesis Students
    • Marco Schuster (2023)
    • Nisha George (2023)
    • Ravil Gasanov (2023)
    • Jyotsna Singh (2023)
    • Paul Krieger (2023)
    • Muneeb Aadil (2023)
    • Mohammad Yaseen
    • Martin Gassner (2022)
    • Saif Ali Khan (2022)
    • Ekatarina Arkhangelskaya (2022)
    • Abraham Ezema (2021)
    • Tim Bruxmeier (2021)
    • Frauke Hinrichs (2021)
    • Sarah Mameche (2021)
    • Jana Hess (2021)
    • Anna Oláh (2020)
    • Edith Heiter (2020)
    • Sandra Sukarieh (2020)
    • Joscha Cueppers (2019)
    • Divyam Saran (2019)
    • Osman Ali Mian (2019)
    • Simina Ana Cotop (2019)
    • Magnus Halbe (2018)
    • Maha Aburahma (2018)
    • Iva Farag-Baykova (2018)
    • Yuliia Brendel (2018)
    • Maike Eissfeller (2018)
    • Boris Wiegand (2018)
    • Tatiana Dembelova (2018)
    • Robin Burghartz (2017)
    • Henrik Jilke (2017)
    • Benjamin Hättasch (2017)
    • Amirhossein Baradaranshahroudi (2016)
    • Apratim Bhattacharyya (2016)
    • Beata Wójciak (2016)
    • Margarita Salyaeva (2016)
    • Manan Gandhi (2016)
    • Kathrin Grosse (2016)
    • Kailash Budhathoki (2015)
    • Panagiotis Mandros (2015)
    • Thomas Van Brussel (2012)
    • Tanja Van den Eede (2011)
    • Sandy Moens (2010)
    • Andie Similon (2010)
    • Sander Schuckmann (2008)
  • Former BSc Thesis Students
    • Rafailia-Maria Chatzianastasiou (2023)
    • Matthias Wilms (2021)
    • Daniel Kindler (2021)
    • Frauke Hinrichs (2017)
    • Magnus Halbe (2016)
    • Stefan Bier (2014)
  • Former Research Assistants
    • Kiet Vo
    • Khánh Hiep Tran
    • Grégoire Pacreau
    • Michael Hedderich
    • Patrick Ferber
    • Shweta Mahajan
    • Tobias Heinen
    • Cristian Caloian
    • David Ziegler
    • Stefan Neumann
    • Andrea Fuksova
    • Eustace Ebhotemhen
    • Shilpa Garg
    • Sinan Bozca
    • Michael Wessely

Selected Recent Publications (go here for the complete list)
2024
Mameche, S, Vreeken, J & Kaltenpoth, D Identifying Confounding from Causal Mechanism Shifts. In: Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR, 2024. (27.6% acceptance rate)project website
Cueppers, J, Krieger, P & Vreeken, J Discovering Sequential Patterns with Predictable Inter-Event Delays. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), AAAI, 2024. (23.8% acceptance rate)project website
Wiegand, B, Klakow, D & Vreeken, J What are the Rules? Discovering Constraints from Data. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), AAAI, 2024. (oral presentation, 2,3% acceptance rate; 23.8% overall)project website
Walter, N, Fischer, J & Vreeken, J Finding Interpretable Class-Specific Patterns through Efficient Neural Search. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), AAAI, 2024. (23.8% acceptance rate)project website
2023
Mameche, S, Kaltenpoth, D & Vreeken, J Learning Causal Models under Independent Changes. In: Proceedings of Neural Information Processing Systems (NeurIPS), PMRL, 2023. (26.1% acceptance rate)project website
Shani, C, Vreeken, J & Shahaf, D Towards Concept-Aware Large Language Models. In: Findings of the Association for Computational Linguistics (EMNLP Findings), ACL, 2023.
Cueppers, J & Vreeken, J Below the Surface: Summarizing Event Sequences with Generalized Sequential Patterns. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), ACM, 2023. (22.1% acceptance rate)project website
Kaltenpoth, D & Vreeken, J Causal Discovery with Hidden Confounders using the Algorithmic Markov Condition. In: Proceedings of the International Conference on Uncertainty in Artificial Intelligence (UAI), AUAI, 2023. (31.2% acceptance rate)project website
Kaltenpoth, D & Vreeken, J Nonlinear Causal Discovery with Latent Confounders. In: Proceedings of the International Conference on Machine Learning (ICML), PMLR, 2023. (27.9% acceptance rate)project website
Mian, O, Kaltenpoth, D, Kamp, M & Vreeken, J Nothing but Regrets — Privacy-Preserving Federated Causal Discovery. In: Proceedings of the 26nd International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR, 2023. (29% acceptance rate)project website
Wiegand, B, Klakow, D & Vreeken, J Why Are We Waiting? Discovering Interpretable Models for Predicting Sojourn and Waiting Times. In: SIAM International Conference on Data Mining (SDM), SIAM, 2023. (27.4% acceptance rate)project website
Kamp, M, Fischer, J & Vreeken, J Federated Learning from Small Datasets. In: Proceedings of the International Conference on Representation Learning (ICLR), OpenReview, 2023. (31.8% acceptance rate)project website
Mian, O, Kamp, M & Vreeken, J Information-Theoretic Causal Discovery and Intervention Detection over Multiple Environments. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), pp 9171-9179, AAAI, 2023. (19.6% acceptance rate)project website
Kaltenpoth, D & Vreeken, J Identifying Selection Bias from Observational Data. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), pp 8177-8185, AAAI, 2023. (oral presentation, 10.8% acceptance rate; 19.6% overall)project website
Coupette, C, Vreeken, J & Rieck, B All the World's a (Hyper)Graph: A Data Drama. Digital Scholarship in the Humanities, pp 1-23, Oxford Academic Press, 2023. (IF 0.8)
2022
Dalleiger, S & Vreeken, J Efficiently Factorizing Boolean Matrices using Proximal Gradient Descent. In: Proceedings of Neural Information Processing Systems (NeurIPS), PMLR, 2022. (25.7% acceptance rate)project website
Mameche, S, Kaltenpoth, D & Vreeken, J Discovering Invariant and Changing Mechanisms from Data. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp 1242-1252, ACM, 2022. (15.0% acceptance rate)
Dalleiger, S & Vreeken, J Discovering Significant Patterns under Sequential False Discovery Control. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp 263-272, ACM, 2022. (15.0% acceptance rate)project website
Hedderich, M, Fischer, J, Klakow, D & Vreeken, J Label-Descriptive Patterns and their Application to Characterizing Classification Errors. In: Proceedings of the International Conference on Machine Learning (ICML), PMLR, 2022. (21.9% acceptance rate)project website
Xu, S, Mian, O, Marx, A & Vreeken, J Inferring Cause and Effect in the Presence of Heteroscedastic Noise. In: Proceedings of the International Conference on Machine Learning (ICML), PMLR, 2022. (21.9% acceptance rate)project website
Wiegand, B, Klakow, D & Vreeken, J Mining Interpretable Data-to-Sequence Generators. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), AAAI, 2022. (15.0% acceptance rate)project website
Coupette, C, Dalleiger, S & Vreeken, J Differentially Describing Groups of Graphs. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), AAAI, 2022. (oral presentation 5.5% acceptance rate; overall 15.0%)project website
Kalofolias, J & Vreeken, J Naming the most anomalous cluster in Hilbert Space for structures with attribute information. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), AAAI, 2022. (15.0% acceptance rate)project website
Cueppers, J, Kalofolias, J & Vreeken, J Omen: Discovering Sequential Patterns with Reliable Prediction Delays. Knowledge and Information Systems vol.64(4), pp 1013-1045, Springer, 2022. (IF 2.822)project website