Meeting Series
Causal Inference for AI
A meeting bringing together researchers interested in causal inference in the Netherlands.
Upcoming Events
Our next quarterly meetings and talks.
No upcoming events scheduled yet, check back soon.
About
Causal Inference for AI (CI4AI) is an informal research community in the Netherlands bringing together researchers from different fields who are interested in causal inference. We meet roughly once every quarter at either TU Delft, Erasmus MC, LUMC or UMC Utrecht. Everyone working on or curious about causal inference is welcome to join. To receive updates on upcoming meetings, please sign up for the mailing list here (note: you will receive a confirmation email to finish signing up).
The meetings are organised by Nan van Geloven (LUMC), Jeremy Labrecque (Erasmus MC), Jesse Krijthe (TU Delft), Oisín Ryan (UMC Utrecht) and Wouter van Amsterdam (UMC Utrecht). If you would like to give a talk, or host a session, please reach out via the contact information below.
Organising institutions
Past Events
Archive of previous meetings and presentations.
- 23 Jun 2026
Quarterly Meeting — June 2026
- Logic and reasoning in causal triangulation: answering causal questions under assumption violations Keling Wang · Erasmus MC
- Improving Observational Conditional Average Treatment Effect Estimation with Average Treatment Effects from Randomized Control Trials Wouter van Amsterdam · UMC Utrecht
- Learning plug-in surrogate endpoints for randomized experiments Jesse Krijthe · TU Delft
- 02 Mar 2026
Quarterly Meeting — March 2026
- Causal inference is not sufficient to infer causation Jeremy Labrecque · Erasmus MC
- Reinforcement Learning for Sustained Behavior Change Support Nele Albers · Tilburg University
- 02 Dec 2025
Seminar on Prediction under Interventions — December 2025
Seminar organised by Ilaria Prosepe and Nan van Geloven
- Self-fulfilling prophecies Wouter van Amsterdam · UMC Utrecht
- Causal blind spots Nan van Geloven · LUMC
- Estimands for sequential prediction under interventions Kim Luijken · Academie Tien & Julius Center, UMC Utrecht
- ABCi benchmarking dataset Ruth Keogh · London School of Hygiene and Tropical Medicine
- Learning Health Systems Daniala Weir · Utrecht University
- Comparison of estimation methods in a diabetes case study Ruth Keogh · London School of Hygiene and Tropical Medicine
- Causal effective sample size Doranne Thomassen · LUMC
- CHARIOT: A prediction-under-intervention model for cardiovascular primary prevention Matthew Sperrin · University of Manchester
- Individualized prediction of platelet transfusion outcomes Ilaria Prosepe · LUMC
- Risk-based cancer screening: a case for prediction under intervention? Vanessa Didelez · Leibniz Institute for Prevention Research and Epidemiology — BIPS
- 27 Oct 2025
Quarterly Meeting — October 2025
- Decisional Analytical Models as Causal Models Maurice Korf · Erasmus MC
- The minimal search space for conditional causal bandits Francisco Simoes · Utrecht University
- CFeval: an R package for counterfactual evaluation of predictions Jasper van Egeraat · LUMC
- 12 May 2025
Quarterly Meeting — May 2025
- Interpreting Black-Box Traffic Forecasting with Counterfactual Explanations. Yanan Xin · TU Delft
- Causally-interpretable meta-analysis using aggregate data Qingyang Shi · University of Groningen
- Evaluating models that predict individualized treatment effect Carolien Maas · LUMC
- 10 Feb 2025
Quarterly Meeting — February 2025
- Methodological challenges in prediction of conditional average treatment effects using RCT data: a case study in pneumonia Jim Smit · Erasmus Medical Center/TU Delft
- Missing confounding information in counterfactual prediction models: an example of model-based clinical evaluation in comparison of radiotherapy techniques in cancer Jungyeon Choi · University Medical Center Utrecht
- Formalization of the complex causal interpretation of hazard contrasts Richard Post · Erasmus Medical Center
- 18 Nov 2024
Quarterly Meeting — November 2024
- Comparing the consistency assumption in different causal frameworks Chang Wei · Erasmus MC
- Robust integration of external control data in randomized trials Rickard Karlsson · TU Delft
- Causal Effect Estimation: A Cross-Moment Approach Saber Salehkaleybar · Leiden Institute of Advanced Computer Science
- 23 Sep 2024
Quarterly Meeting — September 2024
- Augmenting treatment arms with external data through propensity-score weighted power-priors: an application in expanded access. Joost van Rosmalen · UMC Utrecht
- Using Joint Models for Longitudinal and Time-to-Event Data to Investigate the Causal Effect of Salvage Therapy after Prostatectomy Dimitris Rizopoulos · Erasmus MC
- The role of estimands in clinical trials: a case study in oncology Doranne Thomassen · Leiden UMC
- 22 Apr 2024
Quarterly Meeting — April 2024
- Causal Inference Research at Utrecht University Oisín Ryan & Wouter van Amsterdam · UMC Utrecht
- When Do Off-Policy and On-Policy Policy Gradient Methods Align? Davide Mambelli · TU Delft
- Comparing treated patients to controls from separate data sources: misalignment of time zero Rik van Eekelen · Amsterdam UMC
- 15 Jan 2024
Quarterly Meeting — January 2024
- Comparing different treatment strategies in the ICU using observational data Carmen Reep · Erasmus MC
- Detecting hidden confounding in observational data using multiple environments Rickard Karlsson · TU Delft
- Estimating the effect of treatment delay: an extension of multi-state models with g-computation Ilaria Prosepe · LUMC
- 23 Oct 2023
Quarterly Meeting — October 2023
- Carefully Causal: an R function to improve causal inference in applied epidemiology Maurice Korf · Erasmus MC
- Asking: `What If?’ in the Intensive Care: a review of applied causal inference for time-varying treatments Wouter Kant · Radboud University
- Investigating positivity violations in marginal structural survival models: a study on IPTW estimator performance Marta Spreafico · Leiden University
- 21 Feb 2023
Quarterly Meeting — February 2023
- Causal inference and personalized treatment recommendation with prediction rule ensembles Marjolein Fokkema · Leiden University
- Bayesian Reinforcement Learning with Causal Models Frans Oliehoek · TU Delft
- Causality and AI in Marketing: Methods and Applications Sebastian Gabel & Aurelie Lemmens · Erasmus University
- 17 Jan 2023
Quarterly Meeting — January 2023
- Bayesian sensitivity analysis for causal estimation Aad van der Vaart · TU Delft
- TBA Saskia Le Cessie · LUMC
- TBA To be announced · Erasmus MC
- 22 Nov 2022
Quarterly Meeting — November 2022
- From prediction to causal inference and back Nan van Geloven · LUMC
- Causal inference: to get better answers, we need better questions Jeremy Labrecque · Erasmus MC
- Towards Safe Causal Inference Jesse Krijthe · TU Delft
Contact
Want to join, present, or host a meeting?
The community is open to anyone working on or interested in causal inference. There are no membership requirements, just show up!
To get in touch:
- Mailing list — If you want to be kept up to date on upcoming meetings, you To receive updates on upcoming meetings, please sign up for the mailing list here (note: you will receive a confirmation email to finish signing up).
- Give a talk — Please reach out to any of the organisers listed above, for instance send an email to j.h.krijthe@tudelft.nl. Talks are typically 30 minutes including discussion.