# CDSM 2024 — Programme archive Source: https://causalscience.org/archive-2024 PAST EDITIONS / 2024 ## CDSM 2024. 5–6 November 2024 Online Keynote Susan Athey Stanford University [All past editions](https://causalscience.org/archive.html) Browse editions [2025](https://causalscience.org/archive-2025.html) [2024](https://causalscience.org/archive-2024.html) [2023](https://causalscience.org/archive-2023.html) [2022](https://causalscience.org/archive-2022.html) [2021](https://causalscience.org/archive-2021.html) [2020](https://causalscience.org/archive-2020.html) Programme [Day 1 / 5 November](https://causalscience.org/archive-2024#day-1) [Day 2 / 6 November](https://causalscience.org/archive-2024#day-2) ### 5 November 2024 DAY 01 / ONLINE #### Sensitivity Analysis for Causal ML: A Use Case at Booking.com Philipp Bach (University of Hamburg), Victor Chernozhukov (Massachusetts Institute of Technology), Carlos Cinelli (University of Washington), Lin Jia (Booking.com), Sven Klaassen (Economic AI), Nils Skotara (Booking.com), Martin Spindler (Economic AI) #### Causal Inference in Industry (Working) Hanna Post (Henkel Adhesives Technologies) #### DISCO: constrained bandits for personalized discount targeting within fashion e-commerce Jason Shuo Zhang (ASOS.com), Benjamin Howson (Imperial College London), Panayiota Savva (ASOS.com), Eleanor Loh (ASOS.com) #### Structural Causal Models in Strategic Decision-Making Carla Schmitt (Maastricht University), Jermain Kaminski (Maastricht University), Paul Hünermund (Copenhagen Business School) #### Causal Targeting for Mobile Push Notifications Moritz von Zahn (Goethe University Frankfurt), Arda Güler (Goethe University Frankfurt), Kevin Bauer (University of Mannheim), Oliver Hinz (Goethe University Frankfurt) #### Accelerating Experimentation: Bayesian Sequential A/B Testing’s Role in the Tech Industry Richie Lee (Microsoft), Max Knobbout (Uber) #### Causal Inference Tools to Assess the Impact of Marketing and Advertising Initiatives on Key Business Metrics at Bolt Anton Bugaev (Bolt) #### Bridging Causal Discovery and Media Mix Modeling Carlos Trujillo (PyMC Labs), Benjamin Vincent (PyMC Labs) #### Causal Claims in Economics Prashant Garg (Imperial College London), Thiemo Fetzer (University of Warwick & Bonn) #### Fifty Shades of Greenwashing: The Political Economy of Climate Change Advertising on Social Media Bob Kubinec (University of South Carolina), Aseem Mahajan (New York University) #### Assessing the Heterogeneous Impact of Economy-Wide Shocks Marco Dueñas (IMT School for Advanced Studies Lucca), Federico Nutarelli (IMT School for Advanced Studies Lucca), Víctor Ortiz-Giménez (IMT School for Advanced Studies Lucca), Massimo Riccaboni (IMT School for Advanced Studies Lucca), Francesco Serti (IMT School for Advanced Studies Lucca) #### Credit Ratings: Heterogeneous Effect on Capital Structure Helmut Wasserbacher (Novartis), Martin Spindler (Economic AI) #### Learning Structural Causal Models through Deep Generative Models: Methods, Guarantees, and Challenges Audrey Poinsot (Ekimetrics, TAU, LISN, INRIA Saclay), Alessandro Leite (TAU, LISN, INRIA Saclay), Nicolas Chesneau (Ekimetrics), Michèle Sébag (TAU, LISN, INRIA Saclay), Marc Schoenauer (TAU, LISN, INRIA Saclay) #### A Probabilistic Easy Variational Approach to Causal Inference in Complex Datasets Usef Faghih (University of Quebec), Amir Saki (University of Quebec) #### Generalized Criterion for Identifiability of Additive Noise Models Using Majorization Aramays Dallakyan (StataCorp), Yang Ni (Texas A&M University) #### dagrad: A Python Library for Gradient-Based Causal DAG Learning Bryon Aragam (University of Chicago) #### Spillover Reduction Using Cluster-Randomized Experiments: Empirical Evidence and Learnings from Online Gaming Platform Roblox Xiaochen Zhang (Roblox Corporation), Shan He (Roblox Corporation), Yihua Jiang (Roblox Corporation) #### Causal Neuro-Symbolic AI: A Synergy Between Causality and Neuro-Symbolic Methods Utkarshani Jaimini (Artificial Intelligence Institute at University of South Carolina), Cory Henson (Bosch Center for Artificial Intelligence), Amit Sheth (Artificial Intelligence Institute at University of South Carolina) #### Batched Adaptive Team Formation Yan Xu (Virginia Tech), Bo Zhou (Virginia Tech) #### Causal Framework for Building Resilient Supply Chains Karthika Mohan (Oregon State University) #### Towards Causal LLM Agents: Causal Reasoning in LLMs Zhijing Jin (University of Toronto) #### Mining Causality: AI-Assisted Search for Instrumental Variables Sukjin Han (University of Bristol) #### Understanding Problems of Place Through Data: Spatial Causal Inference in Public Administration Research Stephen Kleinschmit Ph.D. (Northwestern University) #### Causal Discovery for Product Analytics Sean Taylor (Motif Analytics) Keynote #### Keynote Susan Athey (Stanford University) ### 6 November 2024 DAY 02 / ONLINE #### Using Causal Machine Learning to Optimize Social Welfare Policies in Kazakhstan: A Case Study on Cash Transfers and Child-Related Outcomes Alibi Jangeldin (NITEC JSC) #### Identifying Successful Interventions Through Break Detection: A New Machine Learning Approach for Generating Hypotheses Patrick Klösel (Potsdam Institute for Climate Impact Research) #### Conflict in a Warming World: How Climate Shocks Impact Rebel Demands and Peace Agreement Outcomes Elisa D'Amico (University of St. Andrews) #### The Heterogeneous Effects of Active Labour Market Policies in Switzerland Federica Mascolo (University of St.Gallen), Nora Bearth (University of St.Gallen), Fabian Muny (University of St.Gallen), Michael Lechner (University of St.Gallen), Jana Mareckova (University of St.Gallen) #### Mostly Harmless Fixed Effects Regression in Python via PyFixest Alexander Fischer (Trivago) #### Bringing Light to the Threshold: Evaluation of Production Policies Using the Regression Discontinuity Design with Application to LED Manufacturing Oliver Schacht (University of Hamburg), Philipp Schwarz (Osram), Sven Klaassen (University of Hamburg, Economic AI), Martin Spindler (University of Hamburg, Economic AI) #### Causal Machine Learning with Counterfactual Prediction: The User’s Guide Aurélien Sallin (SWICA), Daniel Ammann (University of Applied Sciences), Tobias Müller (University of Applied Sciences) #### A Joint Test of Unconfoundedness and Common Trends Martin Huber (University of Fribourg), Eva-Maria Oeß (Universität zu Köln) #### Testing Identification in Mediation and Dynamic Treatment Models Martin Huber (University of Fribourg), Kevin Kloiber (University of Munich), Lukáš Lafférs (Matej Bel University, Norwegian School of Economics) #### Learning Control Variables and Instruments for Causal Analysis in Observational Data Nicolas Apfel (University of Southampton), Julia Hatamyar (University of York), Martin Huber (University of Fribourg), Jannis Kueck (Heinrich Heine University Düsseldorf) #### Manipulation Tests in Regression Discontinuity Design: The Need for Equivalence Testing Jack Fitzgerald (Vrije Universiteit Amsterdam) #### Arguing for Covariate Balance Jeffrey J. Harden (University of Notre Dame) #### NovoGraphs: A Benchmark for Evaluating the Generalizability of LLM-Based Graph Discovery Ashutosh Srivastava (IIIT Hyderabad), Lokesh Nagalapatti (IIT Bombay), Gautam Jajoo (Microsoft Research), Amit Sharma (Microsoft Research) #### The Challenge of Using LLMs to Simulate Human Behavior: A Causal Inference Perspective George Gui (Columbia Business School), Olivier Toubia (Columbia Business School) #### Teaching Transformers Causal Reasoning Through Axiomatic Training Aniket Vashishtha (UIUC), Abhinav Kumar (MIT), Atharva Pandey (Microsoft Research), Abbavaram Gowtham Reddy (IIT), Vineeth N Balasubramanian (IIT), Amit Sharma (Microsoft Research) #### Implicit Personalization in Language Models: A Systematic Study Zhijing Jin (MPI & ETH Zürich), Nils Heil (TUM), Jiarui Liu (Carnegie Mellon), Shehzaad Dhuliawala (ETH Zürich), Yahang Qi (ETH Zürich), Bernhard Schölkopf (MPI), Rada Mihalcea (University of Michigan), Mrinmaya Sachan (ETH Zürich) Roundtable #### Industry Roundtable Evan Peet (Amazon), Micah Gell-Redman (Google), Wenjing Zheng (Roblox), YinYin Yu (LinkedIn) #### Leveraging a Natural Experiment to Estimate the Impact of Customer Satisfaction in Contact Centers Felipe Bahamonde (LATAM Airlines), Paolo Gorgi (acmetric), Hyeokmoon Kweon (Vrije Universiteit Amsterdam), Leandro Magga (LATAM Airlines), Sebastián Orellana (LATAM Airlines) #### Regression Adjustments for Experimental Designs in Two-Sided Marketplaces Timothy Sudijono (Stanford University), Lihua Lei (Stanford University) #### Data Leakage in Recommendation System A/B Tests Roshni Sahoo (Stanford University), Jennifer Brennan (Google Research), Zak Mhammedi (Google Research), Jean Pouget-Abadie (Google Research) #### Large Scale Longitudinal Experiments: Estimation and Inference Apoorva Lal (Netflix), Alex Fischer (Trivago), Matthew Wardrop (Netflix) Podcast #### Causal Bandits Live Podcast Alexander Molak (Causal Bandits Podcast), Ciarán M.Gilligan-Lee (Spotify) Browse editions [2025](https://causalscience.org/archive-2025.html) [2024](https://causalscience.org/archive-2024.html) [2023](https://causalscience.org/archive-2023.html) [2022](https://causalscience.org/archive-2022.html) [2021](https://causalscience.org/archive-2021.html) [2020](https://causalscience.org/archive-2020.html)