Jilles is Faculty (W3) at the CISPA Helmholtz Center for Information Security, where he leads the Exploratory Data Analysis group. He is Honorary Professor of the Department of Computer Science of Saarland University, as well as ELLIS Fellow of the ELLIS Unit Saarbrücken on Artificial Intelligene and Machine Learning.

My research is mainly concerned with causality and unsupervised learning. In particular, I enjoy developing theory and algorithms for answering exploratory questions, such as 'what is going on in my data?' or 'what is going on in my model?' without having to make unnecessary or unjustified assumptions. To identify what is worth knowing, I often employ well-founded statistical methods based on information theory, and then proceed to develop efficient algorithms for extracting useful interpretable results. I like all data types equally much.

Currently I'm investigating techniques for identifying informative and ideally causal structures in large collections of complex data; how to efficiently mine easily interpretable summaries from data; how to determine and discover causal dependencies from observational data; the theoretical and practical foundations of interactive exploration of very large data, discovering things by serendipity; how to mine large relational databases; how to mine very large graphs, including characterising influence propagation in social networks; as well as to study well-founded approaches for meaningfully comparing between, and validation of, explorative results.

Lénaïg Cornanguer is a post-doctoral researcher. Her main research interests are causal inference, discovery of temporal logic from observational data, and explainable anomaly detection.

Lénaïg pursued her PhD at IRISA in Rennes, obtaining her degree from the Université de Rennes 1 for her dissertation titled 'Timed Automata Learning from Time Series' in November 2023. Prior to that, she obtained her Master's of Science in Data Science from the Agrocampus Ouest Engineering School in Rennes, France.

Janis Kalofolias is a post-doctoral researcher. His research interests include many things, ranging from optimistic estimators for subgroup discovery, kernel-based methods for measuring similarities between graphs, to information theoretic methods for subjectively interesting structure from complex data.

Janis obtained his Bachelor of Science in 2011 from the University of Patras, Greece. In 2012 he joined Saarland University to pursue a Master of Science in Computer Science, and was a Research Assistant at the Max Planck Institute for Informatics. He joined the EDA group as a PhD student in November 2016, and defended his dissertation titled 'Subgroup Discovery for Structure Targets' on December 8th 2022.

David Kaltenpoth is a postdoc who works on causal inference under realistic conditions, such as confounding, selection bias, or non-i.i.d. data.

David obtained his Ph.D. in Computer Science from Saarland University on November 25th, 2024. His thesis, 'Don't Confound Yourself: Causality from Biased Data,' was awarded the Helmholtz AI Dissertation Award 2024.

David obtained his Master of Science in Mathematics from the Ludwigs-Maximilian Universität München in 2016. He joined the EDA group in June 2016 for a Research Immersion lab, stayed to do his Ph.D., and is now a postdoc.

Joscha Cüppers is a PhD student who is working on novel methods for mining patterns from data. He is particularly interested in developing methods for discovering interactions and abstractions from sequential data.

Joscha obtained his Bachelor of Science in Computer Science in 2016 from Ulm University and his Master of Science from Saarland University in 2019. He joined the EDA group in 2019 to write his Master's thesis and started his PhD with us in 2020.

Sarah Mameche is a PhD student who is interested in exploratory causal analysis, such as discovering of invariant causal mechanisms from data.

Sarah did both her Bachelor's and Master's degree in Computer Science at Saarland University. She joined the EDA group in 2020 to write her Master's thesis with us on the topic of discovering invariant causal mechanisms between different environments, such as between the populations analyzed by different hospitals. She started her Ph.D. in 2021.

I am a Ph.D. student at CISPA Helmholtz Center for Information Security, supervised by Jilles Vreeken. I am broadly interested in robust and explainable machine learning for large-scale real-world applications. In my Ph.D, I intend to develop new approaches that are at the same time descriptive and predictive. That is the models not only offer predictive capabilities but also facilitate practitioners to gain deeper insights into the problems they are addressing.

I obtained my Bachelor's and Master's degrees in Computer Science from Saarland University. Before joining CISPA, I was a research assistant in the goup of Bernt Schiele at the Max-Planck-Institut for Informatics, supervised by David Stutz . My research focused on adversarial and out-of-distribution robustness of Quantized Neural Networks. I also worked on the influence of Batch Normalization on the vulnerability and generalization capabilities of neural networks.

Sascha Xiaguang Xu is a Ph.D. student who works on the intercept between causality and explainability.

Sascha obtained his Bachelor's and Master's degrees from Saarland University, respectively in 2019 and 2022. During this time he worked with us a student research assistant on the topic of bivariate causal inference in the presence of heteroscedastic noise, which led to an ICML paper in 2022.

Jawad is pursuing a Master's of Science in Data Science and AI at Saarland University. He is currently working on his Master's thesis on the topic of discovering subgroups with exceptional survival characteristics.

Tim is a student in the Saarbrücken Graduate School for Computer Science. He is very broadly interested in all aspects of machine learning, soaking up as much knowledge as he can.

He obtained his Bachelor's degree from Saarland University in 2023 for his thesis 'What makes you say that? Explaining Transformers using Rule Mining and Input Prototyping'in which he showed how we can explain decisions of transformer network through pattern mining.

One of his passions outside of studying is tutoring. Tim was a tutor for Programming 1, Programming 2, the Machine Learning core lecture.

Ben is pursuing his Bachelor's of Science degree in Data Science and AI at Saarland University. He is very broadly interested, and currently seeking a topic for his Bachelor's thesis.

Felix Falkenberg is pursuing a Bachelor's Degree in Computer Science at Saarland University. His research interests revolve around different aspects of explainable machine learning. He is a Student Research Assistant in the EDA group working on developing methods to derive insights into what graph neural networks have learned.

Maya Hilwani is pursuing a Master's of Science in Informatics at Saarland University. She is currently choosing the topic of her Master's thesis. She is very broadly interested, but currently especially so in causality.

Julius is pursuing his Master's of Science degree in Data Science and AI at Saarland University. For his Bachelor's thesis, he investigated how we can learn fully oriented causal models from discrete data.

Tim is pursuing his Master's of Science degree in Data Science and AI at Saarland University. For his Bachelor's thesis, he investigated how we can discover and characterize anomalies identified by deep vision models.

Luis Paulus is pursuing a Master's in Computer Science at Saarland University. He recently handed in his Master's thesis, exploring how we can discover high-quality sets of rules from massive binary datasets through continuous optimization.

Ghada is pursuing a Master's of Science in Data Science and AI at Saarland University. She is currently working on her Master's thesis on continuous-optimization-based approaches for mechanistic interpretability

Hendrik is pursuing a Master's in Informatics and Mathematics at Saarland University. He recently finished his Master's thesis with us on the topic of anomaly detection and repair. He is currently a research assistant, and will start his PhD with us on March 1st 2025.

Matthias Wilms is pursuing a Master's of Science in Informatics at Saarland University. He is currently choosing the topic of his Master's thesis, which will most likely be in the realm of causality. He is additionally a Research Assistant with us working on the topic of scaling up functional dependency discovery such that we can consider massive datasets.

Matthias obtained his Bachelor's of Science in Informatics from Saarland University for his Bachelor Thesis on the topic of efficiently discovering top-k Markov blankets from data that he wrote in the EDA group.