Jilles Vreeken

Prof. Dr. Jilles Vreeken is tenured faculty at the CISPA Helmholtz Center for Information Security, where he leads the Exploratory Data Analysis group. He also serves as an Honorary Professor at Saarland University.

• Research focuses on causal inference, machine learning, and data mining
• Develops unsupervised methods for robust, interpretable models
• PI on grants like HAICU's Neuro-Explicit Models and Crushing Antimicrobial Resistance

His recent work spans causal discovery in non-stationary time series (SPACETIME), federated binary matrix factorization, interpretable neural search patterns, and data modification rule mining from event logs. He applies information-theoretic approaches to address hidden confounding, selection bias, and multi-environment causal modeling.

Key trends in his publications include:

• Integrating causal inference with machine learning via algorithmic Markov conditions
• Advancing federated learning for privacy-preserving causal discovery
• Creating interpretable pattern mining frameworks for graphs, sequences, and high-dimensional data
• Developing MDL-based methods for reliable dependency and rule discovery

Scientific Recognition:

• 2018 - IEEE ICDM Tao Li Award
• 2018 - IEEE ICDM Best Paper
• 2015 - UdS-CS Busy Beaver Teaching Award
• 2011 - ACM SIGKDD Best Student Paper
• 2010 - ACM SIGKDD Doctoral Dissertation Runner-Up
• 2009 - ECML PKDD Best Student Paper

As an educator, he has supervised 15+ PhD/MSc students and taught courses like Topics in Algorithmic Data Analysis and Information-Theoretic Machine Learning. His research group pioneers methods for trustworthy information processing and causal anomaly detection, with applications in materials science, epidemiology, and cybersecurity.