November 4–5 2026, online.
Supported by
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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 4-5, 2026. 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 4–5, 2026 (Online)
Submission Deadline:
September 30, 2026
Acceptance Notification:
October 7, 2026
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.
Teppo Felin is the Ion Presidential Endowed Chair & Co-Director Ion Management Science Lab at the University of Utah, David Eccles School of Business.
Teppo Felin is one of the leading voices connecting causal reasoning, entrepreneurship, strategy, and AI. His recent research challenges purely predictive approaches to decision-making and argues that progress in science, entrepreneurship, and innovation depends on theory-driven causal reasoning, experimentation, and intervention. At a time when causal inference and AI are intertwined, his work offers a distinctive perspective on what humans and intelligent systems can, and cannot, learn from data. From 2013-2021 Felin was a Professor of Strategy at the University of Oxford's Saïd Business School. He also served as the Director of the Oxford Diploma in Strategy & Innovation from 2016 to 2021.
Professor Felin's research focuses on strategy, entrepreneurship, and innovation. This research has been published in journals such as Organization Science, Academy of Management Review, Strategic Entrepreneurship Journal, MIT Sloan Management Review. He has also published articles in scientific outlets such as Psychonomic Bulletin and Review, Perception, Erkenntnis, Plos One, and Genome Biology. Prior to Oxford University and USU, Professor Felin held full-time and visiting academic appointments at Goizueta Business School at Emory University, the Marriott School at Brigham Young University, and Lund University in Sweden. Felin is a native of Helsinki, Finland.
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.
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 2026 at causalscience.org, (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.
