I am a professor at TU Dortmund, leading the Causality group at the Research Center for Trustworthy Data Science and Security and the Department of Statistics, and a PI in the ELLIS Unit NRW. My research is at the intersection of causality and machine learning, focusing on causal discovery, causal representation learning, information theory, and Bayesian deep learning. Prior to my current position, I was a Postdoctoral Researcher Computational Biology Group at ETH Zürich, a Postdoc-Fellow at the ETH AI Center and part of the Medical Data Science Group. I did my PhD in the Exploratory Data Analysis group affiliated with the CISPA Helmholtz Center for Information Security and the Max Planck Institute for Informatics.

News (Causality Group)

• (Jul 2026) New preprint "Large-scale, interpretable gene regulatory network inference through biologically informed matrix factorization" available (preprint)!
• (Jul 2026) Javier presented a poster of his work titled "R2 priors for Grouped Variance Decomposition in High-dimensional Regression" at ISBA'26 (preprint)
• (Jun 2026) Javier gave a talk on "Priors for Grouped Variance Decomposition in High-Dimensional Regression" at NORDSTAT'26
• (May 2026) I am now part of the new ELLIS Unit NRW.
• (Apr 2026) Our paper "Skewness-Robust Causal Discovery in Location-Scale Noise Models" got accepted at ICML'26 (paper)!
• (Apr 2026) Our paper "Regression-Based Estimation of Causal Effects in the Presence of Selection Bias and Confounding" has been accepted to the ECML-PKDD'26 journal track (paper)!
• (Apr 2026) Javier Enrique Aguilar joined the Causality Group as a postdoctoral researcher!
• (Feb 2026) Received a AAAI'26 Outstanding Program Committee Award (Top 0.16%)
• (Sep 2025) Two papers of our group have been accepted to NeurIPS workshops - one on causal inference under selection bias and one on IV regression with high-dimensional treatments.
• (Sep 2025) New paper at TMLR "Two Is Better Than One: Aligned Representation Pairs for Anomaly Detection".
• (Sep 2025) Marlies Hafer and Daniel Klippert presented their work at the PhD Forum at ECML-PKDD.
• (May 2025) I gave an invited talk at the TRR391 at TU Dortmund.
• (Mar 2025) We published a new preprint "Regression-Based Estimation of Causal Effects in the Presence of Selection Bias and Confounding" accompanying the poster we presented at DAGStat 2025.
• (Mar 2025) Our paper "A Cautionary Tale About 'Neutrally' Informative AI Tools Ahead of the 2025 Federal Elections in Germany" got accepted at XAI.
• (Feb 2025) I gave an invited talk at LMU in Munich (invitation by Stefan Feuerriegel).
• (Jan 2025) New paper at TMLR "On the Properties and Estimation of Pointwise Mutual Information Profiles", accompanied with this blogpost by Paweł Czyż.

For more updates access the news arxiv.

Activities

Reviewing for Conferences & Journals

• Area Chair for the International Conference on Artificial Intelligence and Statistics (AISTATS'26, 27)
• Action Editor for the journal Data Mining and Knowledge Discovery (since 2026)
• Expert Reviewer for the European Research Council
• Reviewer for DFG
• Outstanding Program Committee Award at AAAI'26 (Top 0.16%)
• Top 10% reviewer award at NeurIPS'23, AISTATS'22, AISTATS'23
• Reviewer for ICML'22-24, NeurIPS'23-25, ICLR'26, AISTATS'21-25, AAAI'26-27, SDM'21, ECML-PKDD'21, DAMI'22, ISIT'19-20, and sevearal workshops

Invited Talks

• Invited Talk TRR Research Seminar in Dortmund, 2025
• Invited talk at LMU in Munich, 2025
• AIMS Lecture Series, Institute for Artificial Intelligence in Medicine, Essen, 2024
• DoDaS Colloquium, Center for Data Science & Simulation, TU Dortmund, 2024
• Neuro-Mechanistic Modeling group, DFKI Saarbrücken, 2023
• Faculty of Business and Economics, University of Lausanne, 2023
• Statistical Colloquium, TU Dortmund, 2023
• Tutorial at Machine Learning Summer School in Healthcare and Biosciences, 2022
• Data Mining reading group, TU Eindhoven (virtual), 2020
• CWI Machine Learning Seminar, CWI Amsterdam, 2019
• Explanatory Data Analysis group, Leiden University, 2019