Call for Papers
The Causal Data Science Meeting 2023 aims to foster an interdisciplinary dialogue between data scientists from industry and academia regarding causality in machine learning and AI
The Meeting
Causality has long been an important topic in various disciplines such as computer science, economics, social sciences, epidemiology, and philosophy. In recent years, interest has also grown in the business sector with both experimental (A/B testing, reinforcement learning, etc.) and observational causal inference methods (regression methods, instrumental variables, discontinuity designs, causal discovery, etc.) being increasingly applied by practitioners. After the overwhelming success of previous years – with more than 1,900 registered participants in 2022 – we are proud to announce the Causal Data Science Meeting 2023. This two-day virtual conference will bring together academics and data scientists from industry to discuss the latest methodological advances as well as practical aspects and organizational challenges around the adoption of causal ML tools.
The workshop features invited talks and presentations of accepted proposals. Topics of interest include, but are not limited to:
- Advances in causal machine learning and artificial intelligence.
- Data-augmented business decision-making.
- Applications of novel causal inference methods in research and to business-relevant problems.
- Experimentation & A/B testing.
- Causal inference methods in statistics and econometrics.
- Organizational challenges and best practice examples for the implementation of causal inference in industry.
- Insights from practice on challenges and opportunities of causal data science.
- (Open source) software for causal inference.
Keynotes
- Dominik Janzing, Principal Research Scientist, Amazon Research
- Second Keynote, To be announced.
Workshop Date
November 7–8, 2023 (13:00–20:00 Central European Time). The workshop will be online, jointly organized by Maastricht University and Copenhagen Business School.
Submission Deadline
October 1, 2023
Acceptance Notification
October 8, 2023
Submission
Please submit your extended abstract or full paper to submission@causalscience.org. Dual submissions are permitted, i.e. your work is allowed to be previously presented or published at other venues.
(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, we might only ask for sharing your presentation slides.)