PAST EDITIONS / 2025

CDSM 2025.

12–13 November 2025Online

Keynote

Stefan FeuerriegelLMU
All past editions

12 November 2025

DAY 01 / ONLINE

A Counterfactual Analysis of the Dishonest Casino

Martin Haugh (Imperial College), Raghav Singal (Dartmouth College)

Position: Causal Machine Learning Requires Rigorous Synthetic Experiments for Broader Adoption

Audrey Poinsot (INRIA & Ekimetrics), Panayiotis Panayiotou (University of Bath), Alessandro Leite (Normandy University, INSA), Nicolas Chesneau (Ekimetrics), Özgür Şimşek (University of Bath), Marc Schoenauer (TAU, LISN, INRIA)

Causal Inference for Root Cause Analysis in Manufacturing: A causaLens Approach

Ameya Divekar (Michelin), Guillaume Ramelet (Michelin)

Calibration Strategies for Robust Causal Estimation: Theoretical and Empirical Insights on Propensity Score-Based Estimators

Sven Klaassen (Economic AI), Jan Rabenseifner (U of Hamburg), Jannis Kueck (Heinrich Heine University), Philipp Bach (Free University of Berlin)

Learning and Testing Exposure Mappings of Interference using Graph Convolutional Autoencoder

Martin Huber (University of Fribourg), Jannis Kuek (University of Fribourg), Mara Mattes (Heinrich Heine University)

Substitution Effects in Fashion Retail Demand

Evgenii Ozhegov (Zalando)

Seeking External Advice – Which Firms in Emerging Markets Hire External Consultants?

Marek Giebel (Copenhagen Business School), Alexander Lammers (FOM)

Do Zombie Firms Really Cause Congestion?

Norbert Ernst (Austrian National Bank), Michael Sigmund (Austrian National Bank)

Policy Learning in Practice: Simulation Evidence and a Case Study of Optimal Allocation of Subsidised Health Insurance

Julia Hatamyar (University of York), Noemi Kreif (University of Washington)

Convergence of Q-Learning Under Relative Ignorability

Mary Lena Bleile (Sanofi)

Precision Gains from Temporal Switchback Designs for Seat-Ancillary Pricing Experiments at LATAM Airlines

Nicolas Ferrari Ortiz (LATAM Airlines), Sebastian Orellana (LATAM Airlines), Timur Abbiasov (ADC), Marie Garkavenko (ADC), Rutger Lit (ADC)

Improving Empirical Models in Strategic Management Research with Double Machine Learning

Rylan Miller (University of Maryland), Evan Starr (University of Maryland)

Causal AI Scientist: Facilitating Causal Data Science with Large Language Models

Vishal Verma (Carnegie Mellon University), Sawal Acharya (Stanford University), Samuel Simko (ETH Zürich), Devansh Bhardwaj (IIT Roorkee), Anahita Haghighat (Independent), Mrinmaya Sachan (ETH Zurich), Dominik Janzing (Amazon), Bernhard Schölkopf (MPI for Intelligent Systems, Tübingen), Zhijing Jin (MPI for Intelligent Systems, Tübingen, University of Toronto, Vector Institute)

Special session

Causal Bandits Special: Do Heterogeneous Treatment Effects Exist?

Alex Molak (Causal Python), Stephen Senn (Independent Statistician), Richard Hahn (Arizona State University)

DAG It: Drawing Assumptions Before Conclusions Changes Results

Michael Denly (Texas A&M University), Graham Goff (Texas A&M University)

Debiased Front-Door Learners for Heterogeneous Effects

Yonghan Jung (University of Illinois Urbana-Champaign)

Non-overlap Average Treatment Effect Bounds

Herbert P. Susmann (New York University), Alec McClean (New York University), Iván Díaz (New York University)

Compound Causal Selection Decisions: An Almost SURE Approach

Jiafeng Chen (Stanford University), Lihua Lei (Stanford University), Timothy Sudijono (Stanford University), Liyang Sun (University College London), Tian Xie (University College London)

13 November 2025

DAY 02 / ONLINE

Avoiding Mistakes in Measuring the Impact of AI

Quentin Gallea (Independent)

Treatment Effect Estimators as Weighted Outcomes

Michael Knaus (University of Tübingen)

Federated Causal Inference beyond Meta-Analysis in RCTs and Observational Studies

Remi Khellaf (INRIA)

Quantile Individualized Average Treatment Effect

Johanna Kutz (University of St. Gallen), Michael Lechner (University of St. Gallen)

Sensitivity Analysis for Treatment Effects in Difference-in-Differences Models using Riesz Representation

Philipp Bach (FU Berlin), Victor Chernozhukov (MIT), Sven Klaassen (University of Hamburg, Economic AI), Jannis Kueck (Heinrich Heine University Düsseldorf), Mara Mattes (Heinrich Heine University Düsseldorf), Martin Spindler (University of Hamburg, Economic AI)

Causal Science Assistant

Lokesh Nagalapatti (Microsoft Research), Grace Sng (Carnegie Mellon University), Amit Sharma (Microsoft Research)

Unsupervised Discovery of Causal Mechanisms for Management Research

Marco Barbero Mot (Vanderbilt University), Danilo Messinese (IE University)

Sensitivity Analysis for Quasi-Experimental Methods

Carlos Trujillo (PyMC Labs), Anton Bugaev (Bolt)

Open Causal: a FAIR Platform for Causal Graphs

Hüseyin Küçükali (Utrecht University)

CausalPFN: Amortized Causal Effect Estimation via In-Context Learning

Vahid Balazadeh (University of Toronto, Vector Institute), Hamidreza Kamkari (Layer 6 AI), Valentin Thomas (Layer 6 AI), Benson Li (University of Toronto, Vector Institute), Junwei Ma (Layer 6 AI), Jesse C. Cresswell (Layer 6 AI), Rahul G. Krishnan (University of Toronto, Vector Institute)

Paper / abstract

Compound Causal Inference for Binomial Outcomes

Yan Chen (Duke University), Lihua Lei (Stanford University)

Paper / abstract

Echoes of the Ping: How Push Notifications Shape App Engagement and its Implications for Targeting

Moritz von Zahn (Goethe University Frankfurt), Arda Güler (Goethe University Frankfurt), Kevin Bauer (Goethe University Frankfurt), Oliver Hinz (Goethe University Frankfurt)

Paper / abstract

The Impacts of Optimal Bandwidths in Regression Discontinuity Design

Jack Fitzgerald (Vrije Universiteit Amsterdam)

Evaluating Program Sequences with Double Machine Learning: An Application to Labor Market Policies

Fabian Muny (University of St. Gallen)

Paper / abstract

Are Cash Reallocations Effective Amid Multiple Shocks? A Double Selection Approach

Ellestina Jumbe (University of Rome Tor Vergata, United Nations)

Paper / abstract

Forests for Differences: Robust Causal Inference Beyond Parametric DiD

Hugo Gobato Souto (Luizalabs), Francisco Louzada Neto (University of Sao Paolo)

Paper / abstract

A Debiased Estimator for the Mediation Functional in Ultra-High Dimensional Setting in the Presence of Interaction Effects

Shi Bo (Boston University), Amir Emad Ghassami (Boston University), Debarghya Mukherjee (Boston University)

Paper / abstract

Discovering Causal Relationships Between Time Series with Spatial Structure

Rebecca F. Supple (University of St Andrews), Hannah Worthington (University of St Andrews), Ben Swallow (University of St Andrews)

Paper / abstract

The Effects of Flipped Classrooms in Higher Education: A Causal Machine Learning Analysis

Daniel Czarnowske (Heinrich Heine University Düsseldorf), Florian Heiss (Heinrich Heine University Düsseldorf), Theresa M.A. Schmitz (Heinrich Heine University Düsseldorf), Amrei Stammann (University of Bayreuth)

Paper / abstract

Causal Mediation in Natural Experiments

Senan Hennessy (Cornell University)

Paper / abstract

Leveraging Double/Debiased Machine Learning to Improve Meta-Analyses

Adam Hardaker (University of Kassel)

Paper / abstract
Keynote

Generating Impact with Causal ML: Applications, Strengths, and New Opportunities

Stefan Feuerriegel (LMU)

Power Analysis is Essential: High-Powered Tests Suggest Minimal to No Effect of Rounded Shapes on Click-Through Rates

Ron Kohavi (Independent), Jakub Linowski (GoodUI), Lukas Vermeer (Vista), Fabrice Boisseranc (Kameleoon), Joachim Furuseth (Coop Norway), Andrew Gelman (Columbia University), Guido Imbens (Stanford University), Ravikiran Rajagopal (United Parks & Resorts)

Interpretable Personalization in Large-Scale Digital Experiments

Naveen Basavanhally (Intuit)

Adaptive Experimentation: Bandits & Paid Marketing

Tilman Drerup (Instacart)

Enhancing Engagement Metric Sensitivity in Online Experiments via Machine Learning-Based Variance Reduction

Minha Hwang (Microsoft)