Jilles is Tenured Faculty at the CISPA Helmholtz Center for Information Security, where he leads the Exploratory Data Analysis group. In addition, he is affiliated as Senior Researcher with the Database and Information Systems group of the Max Planck Institute for Informatics, as well as Professor at the Department of Computer Science of Saarland University.

His research is mainly concerned with exploratory data mining and interpretable machine learning. That is, developing theory and algorithms for summarising data in easily understandable terms. To identify what you need to know, i.e., what is the most interesting structure in the data, he often employs information theoretic methods. In particular, the principles of Minimum Description Length (MDL) and Maximum Entropy have proven to be highly valuable tools.

Currently he is investigating techniques for identifying informative local structures in large collections of complex data; how to efficiently mine good data descriptions directly such data; how to mine very large graphs, including characterising influence propagation in social networks; and, last but not least, how to determine cause and effect, i.e. causal inference and modelling.

Michael is a post-doctoral researcher affiliated with the Exploratory Data Analysis group, as well as with the Department of Data Science and AI at Monash University, Melbourne.

His research focusses on theoretically sound, efficient, and trustworthy machine learning. In particular, he is interested in learning theory, as well as sound parallel, distributed, and federated learning.

He currently works on the theory of deep learning, linking properties of the loss surface to a networks generalization abilities. He also works on trustworthy federated learning that enables its confident application even in critical scenarios, like autonomous driving and healthcare.

Panagiotis Mandros is a post doc in the EDA group. His research interests include combining probabilistic and information theoretic methods to discover knowledge from complex data.

Panagiotis obtained his Bachelor of Science in 2012 from Aristotle University of Thessaloniki, Greece. In 2013 he joined Saarland University to pursue a Master of Science in Computer Science as an IMPRS-CS student. He joined the EDA group in October 2014 as a Research Assistant. In 2015 he was awarded an honours degree for his thesis 'Information-Theoretic Supervised Feature Selection for Continuous-Valued Data'. He pursued his PhD supported by a scholarship from IMPRS, and on March 4th 2021 successfully defended his thesis titled 'Discovering Robust Dependencies from Data', obtaining the grade 'Summa Cum Laude'.

Corinna Coupette is a PhD student at the Max Planck Institute for Informatics, working on theory and methods for graph analysis. Her research focuses on methods for interpretable graph similarity assessment and theory for model-agnostic graph algorithms. As a recovering lawyer, she is also involved in a number of interdisciplinary data science projects aiming to measure the law. More details, including a full list of publications, can be found at here.

Corinna holds a B.Sc. in Computer Science from LMU Munich and an M.Sc. in Computer Science from Saarland University. She received a Ph.D. in Law from Bucerius Law School in Hamburg with a dissertation on "Legal Network Science", for which she was awarded the 2018 Bucerius Dissertation Award and the 2020 Otto Hahn Medal of the Max Planck Society. Before starting her Ph.D. in Computer Science, she joined the EDA group as a research assistant in 2019.

Joscha Cüppers is a PhD student at the Saarland Graduate School of Computer Science and funded by CISPA Helmholtz Center for Information Security. He is working on pattern mining in temporal settings. Particular he is interested in developing methods to find interactions between time series as well as describing change, in an interpretable way, over time.

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 originally joined the EDA group for his master thesis, and started his PhD in 2020.

Sebastian Dalleiger is a PhD student of the Saarbrücken Graduate School for Computer Science, funded by the CISPA Helmholtz Center for Information Security. In addition he is affiliated with the Department for Databases and Information Systems at the Max Planck Institute for Informatics. His research interests include data mining and machine learning, and in particular information theoretic approaches to extracting useful models form data.

Sebastian obtained his Bachelor of Science in Mathematics from the University of Marburg in 2012, and his Master of Science in Computer Science from Saarland University in 2015. He joined the EDA group as a PhD student in September 2017.

Jonas Fischer is a PhD student funded by the International Max Planck Research School for Computer Science (IMPRS-CS), as well as a student in the Saarbrücken Graduate School for Computer Science. His interests range from Data Mining to Explainable Machine Learning, with his main focus on making pattern languages more expressive in theory, and how to use patterns to explain ML models, such as Neural Networks, in practice.

Jonas obtained both his Bachelor of Science and his Master of Science in Bioinformatics from Saarland University, respectively in 2015 and 2017. He joined the EDA group in April 2016 for a Research Immersion lab, and started his PhD in 2017.

Janis Kalofolias is a PhD student of the Saarbrücken Graduate School for Computer Science, funded by the CISPA Helmholtz Center for Information Security. In addition he is affiliated with the Department for Databases and Information Systems at the Max Planck Institute for Informatics. 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.

David Constantin Kaltenpoth is a PhD student funded by the CISPA Helmholtz Center for Information Security, member of the International Max Planck Research School for Computer Science, and a student of the Saarland University Graduate School of Computer Science. His research focus is on information theoretic approaches to causal inference.

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, and started his PhD in October 2017.

Sarah Mameche is a PhD student at the Saarland Graduate School of Computer Science and funded by CISPA Helmholtz Center for Information Security. She is working on the topic of exploratory causal analysis, including causal inference and the discovery of stable mechanisms.

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

Osman Ali Mian is a PhD student in the EDA group. His research interests include causal inference, data mining, and machine learning.

Osman obtained his Bachelor's degree in 2015 from National University of Computer and Emerging Sciences (NUCES) in Karachi, Pakistan. In 2017 he joined Saarland University to pursue a Master of Science in Computer Science. He joined the EDA group in September 2018 as a Research Assistant, and finished his Master thesis titled 'Causal Discovery using MDL-based Regression' in July 2019.

Boris is a PhD student in the EDA group, working on knowledge extraction from event logs. His research aims at developing methods to mine understandable models from complex event data. Application fields of his research include initial understanding of the control-flow in manufacturing and business processes, anomaly detection and bottleneck detection.

Boris obtained his Bachelor’s degree in Applied Computer Sciences at the University of Applied Sciences in Saarbrücken. In 2018, he completed his Master’s degree in Computer Science at Saarland University. After a year of practical work, he joined the EDA group in 2019. He is employed as a Data Scientist at AG der Dillinger Hüttenwerke and pursues to combine the best of research and industrial application.

Muneeb Aadil pursues a Masters in Computer Science at Saarland University, and holds a scholarship from the International Max Planck Research School in Computer Science (IMPRS-CS). He is currently working on his Master thesis on the topic of learning causal invariants from temporal data.

Ekaterina Arkhangelskaya is a student of the Saarland Graduate School for Computer Science. She is currently pursuing her Master thesis in the EDA group, working on the topic of robust learning in neural networks.

Tim Bruxmeier is pursuing a Master of Science in Computer Science at Saarland University. He is currently working on this Master thesis with us on the topic of clustering attributes using total correlation. Previously, he did his Bachelor of Science also at Saarland University, and wrote his thesis on the topic of image textures comparison.

Abraham Obiwanne Ezema is pursuing his M.Sc. degree in Computer Science at Saarland University. He is currently both a Research Assistant in the EDA group working on the topic of rich latent factor modelling for detecting confounding, as well as working on explainability of deep neural networks for his Master thesis.

Martin Gassner is pursuing a Master of Science in Informatics at Saarland University. He is currently working with us on his Master Thesis.

Prior to his Masters in Saarbrücken, Martin did his BSc at the University of Maastricht, the Netherlands.

Frauke Hinrichs is pursuing her Master of Science in Informatics at Saarland University. She did her Bachelor thesis with us on on the topic of joint summarisation of multiple sequence databases, after which she worked as a Research Assistant on the same topic. She is currently working on her Master thesis, which is about discovering meaningful patterns from music.

Saif Ali Khan is pursuing a Master of Science in Informatics at Saarland University. He is currently working with us on his Master Thesis, which will be on the topic of causal shapley values for better interpretability of machine learning models.

Before starting his Masters degree in Saarbrücken in 2019, he obtained his Bachelor's degree in 2018 from Ghulam Ishaq Khan Institute (GIKI) in Topi, Pakistan.

Daniel Kindler is pursuing a Master of Science in Informatics at Saarland University. He is currently a Research Assistant with us, working on the topic of how to discover meaningful low-dimensional embeddings of high-dimensional data.

Daniel did his Bachelor in Computer Science at Saarland University, and wrote his Bachelor Thesis with us on the topic of discovering density-preserving low dimensional embeddings.

Jyotsna Singh is pursuing a Master of Science in Informatics at Saarland University. She is currently working with us as a Research Assistant, as well as on her Master Thesis. The topic of the latter is on explaining transformers.

Before starting her Masters in Saarbrücken in 2018, she finished her BSc in Electrical Engineering at IIT Kharagpur in 2017, interned at Nanyang University Singapore in 2016, and the Max Planck Institute for Informatics in 2017.

Matthias Wilms is pursuing a Bachelor of Science in Informatics at Saarland University. For his Bachelor Thesis he is currently working with us on the topic of efficiently discovering top-k Markov blankets from data.

Sascha Xiaguang Xu is currently pursuing a Master of Science in Informatics at Saarland University. His research interests including data mining, machine learning, and causal inference. He is a research assistant in the EDA group, working on the topic of causal inference in the bivariate case.

Mohammad Yaseen Aftab pursues a Master degree in Computer Science at Saarland University, and holds a scholarship from the International Max Planck Research School in Computer Science. As a Research Assistant he is working on the discovery of anomalies in temporal data, and for his Master thesis he is exploring robustness in light of causal learning.