he/himJonas Wahl
Senior Researcher
Group Leader Causal Models and Representations (CaMoRe)
Professor II for Causal Analysis and Artificial Intelligence (University of Bergen)
DFKI – Neuro-Mechanistic Modeling
CaMoRe – Causal Models and Representations
University of Bergen
CERTAIN – Center for European Research in Trusted AI
DFKI Labor Berlin
Kesselhaus in der Lanolinfabrik - Salzufer 15/16
10587 Berlin
Germany
About Me
Originally trained as a mathematician, I have become interested in causal inference through the famous ‘Book of Why’. Nowadays, my research focuses on causal discovery evaluation, causal abstraction, causally informed sequential decision making, as well as methods that combine experimental and observational data for inference. I like to work together closely with domain scientists; at the moment I focus on applications in ecology and health, but I am open to working in other domains. If you want to collaborate, please get in touch!
I am one of the project leaders of the MAC-MERLin project and the head of the research group Causal Models and Representations (CaMoRe). Since February 2026, I am also a part-time Professor II for AI and Causal Analysis at the University of Bergen, Norway.
Before joining DFKI in 2025, I was a postdoctoral researcher at TU Berlin (2022–2024, with Prof. Jakob Runge), working on causal inference for spatio-temporal data in climate science, the evaluation of causal discovery, and the statistical foundations of causal inference. Before that, I was a postdoc at the Hausdorff Center for Mathematics in Bonn (2019–2022), working on stochastic processes on branching graphs and random walks in algebras, after completing my Ph.D. in mathematics at KU Leuven (2018) under the supervision of Prof. Stefaan Vaes.
Other Work / Research Activity
Scientific Community Service
- Guest editor (2025–2027) of a special issue on Causal Inference in Ecology and Evolutionary Biology in Philosophical Transactions of the Royal Society B.
- Workshop and conference organization:
- Saarbrücken Causality Workshop (DFKI, October 2026), co-organized with researchers from DFKI and CISPA.
- CAESAR – Causal Anomalies: Exploring Synergies of Anomaly Detection and Causal Inference at ECML PKDD 2026 (Naples), co-organized with the DLR Institute of Data Science in Jena.
- CI4TS – Causal Inference for Time Series at UAI 2023 (Pittsburgh) and UAI 2024 (Barcelona).
- Young Women in C*-algebras and Young Mathematicians in C*-algebras 2018 (KU Leuven).
- Program committee of STCausal 2024, the 1st ACM SIGSPATIAL International Workshop on Spatiotemporal Causal Analysis (Atlanta).
- Reviewer for NeurIPS, ICML, AAAI, UAI, CLeaR, Science Advances, Nature Communications, Chaos, Journal of Causal Inference, Annals of Epidemiology, IEEE Transactions on Signal Processing and Communications in Mathematical Physics.
- I am a member of Algoright e.V..
Previous Affiliations
- Fellow at the Centre for Interdisciplinary Research (ZiF) Bielefeld within the focus program Mapping Evidence to Theory in Ecology (2024).
- Associated member of the ELLIS Unit Jena (2023–2024).
- Long-term guest researcher at the German Aerospace Center (DLR) in Jena (2022–2024).
Selected Talks
- Isaac Newton Institute, University of Cambridge, March 2026
- Einstein Circle Berlin, Charité, February 2026
- IKIM Essen, December 2025
- Winter School on Causality and Explainable AI, Paris, October 2025
- University of Nancy, September 2025
- Symposium on Causal Inference, University of Potsdam, June 2025
- Workshop Addressing the Challenges of Generalization and Causality, University of Bielefeld, November 2024
- Statistics Seminar, University College Dublin, October 2024
- Workshop Causal and Safe Reinforcement Learning, DFKI Saarbrücken, May 2024
- Workshop Causal Spatial Data Analysis, Schloss Dagstuhl, May 2024
- Workshop Taming Complexity in Ecology, February 2024
- Statistics Seminar, HU Berlin, January 2024
- Workshop Fundamental Challenges in Causality, University of Grenoble, May 2023
- USMILE Workshop, University of Valencia, October 2022
Interests
- Causal Inference
- Causal Discovery
- Evaluation and Benchmarking
- Causal Abstraction
- Causal Sequential Decision Making
- Applications in Health
- Applications in Ecology
Education
Doctor of Science (Ph.D.) in Mathematics, 2018
Supervised by Prof. Stefaan Vaes at KU Leuven, Belgium
Nonsingular Bernoulli actions and quantum symmetries
Master of Science in Mathematics, 2014
Saarland University, Germany
Bachelor of Science in Mathematics, 2012
Saarland University, Germany
Publications (16)
2026
How PC-based Methods Err: Towards Better Reporting of Assumption Violations and Small Sample Errors
2026 — Proceedings of the 42nd Conference on Uncertainty in Artificial Intelligence
Chaotic and complex dynamics expose the limits of counterfactual reasoning
2026 — Scientific Reports (Sci Rep)
2025
Sortability of Time Series Data
2025 — Transactions on Machine Learning Research (TMLR)
Structural Causal Bottleneck Models
2025 — UAI 2025 Workshop on Causal Abstractions and Representations. Causal Abstractions and Representations (CAR), located at UAI 2025, July 25, Rio de Janeiro, Brazil
Separation-Based Distance Measures for Causal Graphs
2025 — Proceedings of The 28th International Conference on Artificial Intelligence and Statistics. International Conference on Artificial Intelligence and Statistics (AISTATS-2025), May 3-5, Mai Khao, Thailand
The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications
2025 — Proceedings of the Fourth Conference on Causal Learning and Reasoning. Conference on Causal Learning and Reasoning (CLeaR-2025)
2025 — Proceedings of the Fourth Conference on Causal Learning and Reasoning. Conference on Causal Learning and Reasoning (CLeaR-2025)
2024
Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions
2024 — Proceedings of the Third Conference on Causal Learning and Reasoning. Conference on Causal Learning and Reasoning (CLeaR-2024)
Causal Inference for Spatial Data Analytics (Dagstuhl Seminar 24202)
2024 — Dagstuhl Reports
2023
Vector Causal Inference between Two Groups of Variables
2023 — Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)
2022
2022 — Journal of the London Mathematical Society
Conditional Independence Testing with Heteroskedastic Data and Applications to Causal Discovery
2022 — Advances in Neural Information Processing Systems 35. Neural Information Processing Systems (NeurIPS-2022), 36th Conference, November 28 - December 9
2018
Nonsingular Bernoulli actions & quantum symmetries
2018 — ARENBERG DOCTORAL SCHOOL Faculty of Science
2015
A note on reduced and von Neumann algebraic free wreath products
2015 — Illinois Journal of Mathematics (IJM)
Teaching (6)
Spatiotemporal Models and Inference
Lecturer (English), in Summer 2025
Seminar at Saarland UniversityCausal Inference
Lecturer (Joint With Prof. Jakob Runge and Dr. Urmi Ninad) (English), in Winter 2023/24
Lecture at TU BerlinCausal Inference
Lecturer (Joint With Prof. Jakob Runge and Dr. Urmi Ninad) (English), in Winter 2022/23
Lecture at TU BerlinProbability Theory I
External Lecturer (Dutch), in Summer 2020
Lecture at KU LeuvenIntegrable Probability
Substitute Lecturer (4 of 16 Lectures)
Lecture at HCM BonnFunctional Analysis II
Guest Lecturer (5 Lectures), in Winter 2015/16
Lecture at Saarland University
Supervised Students (12)
Pascal Schumann
PhD Thesis, ongoing
Felix Jahn
PhD Thesis, ongoing
Christopher Lohse
PhD Thesis, ongoing
Raphael Franke
PhD Thesis, ongoing
Simon Bing
Phd - Postdoctoral Supervision, ongoing
Sirisha Sandadi
Master's Thesis, ongoing
Ruoxuan Liu
Binding Affinity Prediction with Deep Learning: Structural Learning or Dataset Bias?
Master's Thesis, 2026
Pascal Schumann
Learning Continuous Dosage Strategies for Sepsis via Offline Reinforcement Learning
Master's Thesis, 2026
Johannes Isle
Learning Causal Graphs via Discrete, Order Based Search: The FLOP Algorithm
Bachelor's Thesis, 2026
Nicolas-Domenic Reiter
Structural equation processes - A linear model for causal inference in discrete-time
Phd - Postdoctoral Supervision, 2025
Hannah Westhoff
Free probability, (*q*, *t*)-deformed processes, and applications
Master's Thesis, 2022
Matthias Valvekens
Representation theory for non-extremal subfactors and their standard invariants
Master's Thesis, 2016