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November 12–13 2025, online.
Supported by
Causality has long been an important topic in various disciplines including computer science, economics, the social sciences, epidemiology, and philosophy. In recent years, interest has also grown in the business sector with both experimental (such as A/B testing, reinforcement learning, business experimentation) and observational causal inference methods (such causal discovery, root-cause analysis, quasi-experimental methods) being increasingly applied by practitioners.
Ever since its launch, the Causal Data Science Meeting has been at the forefront of this development, connecting a global audience of causality experts from academia and industry. We are excited to announce this year's Causal Data Science Meeting, which will take place as a two-day virtual conference on November 12-13, 2025. The event will focus on the newest methodological advances, practical aspects, and organizational challenges related to the adoption of causal machine learning tools. It will feature invited talks and presentations of accepted proposals.
Workshop Date:
November 12–13
Submission Deadline:
September 30
Acceptance Notification:
October 7
Please submit your presentation proposal, extended abstract or full paper to submission@causalscience.org
The meeting is organized as a workshop for the purpose of facilitating discussion and disseminating ideas. No conference proceedings of accepted presentations will be published. If you want to register as a participant, without presenting, please click here.
If your organization would like to sponsor the event, please contact us at contact@causalscience.org.
Stefan Feuerriegel heads the new Institute of Artificial Intelligence (AI) in Management. He holds a dual affiliation as a full professor at LMU Munich School of Management and the Faculty of Mathematics, Informatics, and Statistics at LMU Munich.
In 2024, he visited the Stanford University in the USA as a Visiting Scholar. In 2025, he was a visiting scholar at the Cambridge Centre for AI in Medicine (CCAIM) at the University of Cambridge.Previously, Stefan was an assistant professor at ETH Zurich. He gaduated in 2015 with a Ph.D. at the Chair for Information Systems Research (Prof. Dr. Dirk Neumann), University of Freiburg. Stefan has co-authored 70+ journal articles and 80+ peer-reviewed conference papers. These works have appeared in top outlets from general science (e.g. Nature, PNAS), management (e.g Management Science, Marketing Science) and machine learning (e.g. NeurIPS, ICML, ICLR, WWW, KDD, ACL, EMNLP, AAAI). Stefan currently serves as methodological expert for the Academy of Management Journal (AMJ). His group is supported by various companies (e.g. Google, Microsoft, Oracle, Nvidia, Amazon) and multiple grants, for which the funding volume totals to more than EUR 5.5 million. In particular, he received an SNSF Eccellenza Grant, which is the equivalent in Switzerland to the ERC Starting Grant.
Explore cutting-edge methodologies and engage in discussions about the role and impact of causality in machine learning.
Bridge the gap between theory and practice by exploring real-world applications of causal data science.
Understand the role of causality for fairness, robustness, and discrimination in policy-making.
Image: ID 241391100 © Evgeny Turaev | Dreamstime.com
The Causal Data Science Meeting was founded in 2020 and thought as as a small-scale workshop for 50 attendees. However, already in its first year, CDSM received an overwhelming response of 900 pre-registrations, which encouraged us to continue the event annually. We aim to create a friendly, efficient, and constructive environment for academics and practitioners to exchange ideas on all causality-related topics in data science and machine learning. We strive to maintain transparency in our non-profit goal and use all sponsorships received to cover smaller expenses and PhD research.
Participants since 2020
Accepted presentations
Become a Sponsor
Sponsors of the event will be displayed on the conference website and conference materials, with an opportunity to provide further information and job postings in the field of causal data science. During the last conference, sponsors had an exposure to more than 1.200 online participants.
What you get: Logos of the sponsoring company on the conference website of the Causal Data Science Meeting 2025 at causalscience.org (October 01 onwards), (b) visibility on presentation slides of the main conference (Welcome, Keynotes, Breaks; November 5-6), and (c) a short profile of the company , including links to three sponsor’s job postings related to causal inference. Proceeds from sponsoring are used to cover opearating expenses and research for/with PhDs.
