PAST EDITIONS / 2022

CDSM 2022.

7–8 November 2022Online

Keynotes

Judea PearlUCLA

Silvia ChiappaDeepMind & UCL

All past editions

7 November 2022

DAY 01 / ONLINE

Bounding counterfactuals under selection bias

Alessandro Antonucci (IDSIA, Lugano, CH)

A proposed theoretical framework for retinal biomarkers

Ian MacCormick (Centre for Inflammation Research, University of Edinburgh, The Queen’s Medical Research Institute, UK)

Quantitative probing: Validating causal models with quantitative domain knowledge

Daniel Grünbaum (OSRAM Group & University of Regensburg, DE)

Leveraging causal relations to provide counterfactual explanations and feasible recommendations to end users

Riccardo Crupi (Intesa Sanpaolo, IT)

The interventional Bayesian Gaussian equivalent score for Bayesian causal inference with unknown soft interventions

Giusi Moffa (Department of Mathematics and Computer Science, University of Basel, CH & Division of Psychiatry, University College London, London, UK)

The importance of hyperparameter tuning in causal effect estimation

Damian Machlanski (Department of Computer Science and Electronic Engineering, University of Essex, UK)

Testing the identification of causal effects in observational data

Jannis Kueck (University of Hamburg, Faculty of Business Administration, DE)

Explainable Bayesian networks applied to transport vulnerability

Alta de Waal (Department of Statistics, University of Pretoria, SA & Centre for Artificial Intelligence Research (CAIR), SA)

Benchpress: A scalable and versatile workflow for benchmarking structure learning algorithms

Jack Kuipers (ETH Zurich, CH)

Differentiable causal discovery under latent interventions

Goncalo Faria (Instituto Superior Tecnico & LUMLIS (Lisbon ELLIS Unit), Universidade de Lisboa, PT)

Learning Bayesian networks through Birkhoff polytope: A relaxation method

Aramayis Dallakyan (StataCorp, US)

Image-based treatment effect heterogeneity

Connor Jerzak (University of Texas at Austin, Department of Government, US)

Applying causal AI to industrial use cases

Stuart Frost (Geminos, US)

A dynamic bayesian model for causal inference with mediation

Ho Kim (University of Missouri-St. Louis, US)

Orthogonal policy learning under ambiguity

Riccardo d’Adamo (University College London, Department of Economics, UK)

An open-source suite of causal AI tools and libraries

Emre Kiciman (Microsoft Research, US)

Keynote

Judea Pearl (UCLA)

Roundtable

Causal science in the industry: A roundtable with industry leaders

Victor Zitian Chen (Director of Experimental Design and Causal Inference, Fidelity Investments), Sathya Anand (Director of Data Science and Engineering, Netflix), Somit Gupta (Principal Data Scientist at Experimentation Platform, Microsoft), Mikael Konutgan (Software Engineering Manager at Experimentation Platform, Meta), Benjamin Skrainka (Data Science Manager in Experimentation, eBay), Eric Weber (Senior Director of Data Science, Experimentation, Causal Inference & Platform, Stitch Fix), YinYin Yu (Applied Research Manager, Experimentation & Causal Inference, LinkedIn)

8 November 2022

DAY 02 / ONLINE

Effect or treatment heterogeneity? Policy evaluation with aggregated and disaggregated treatments

Michael Knaus (University of Tübingen & IZA, Bonn, DE)

Can causal graphs improve estimation with Double Machine Learning?

Patrick Rehill (Centre for Social Research and Methods, Australian National University, AU)

So many choices in Double Machine Learning!? Practical insights from an extensive simulations study

Oliver Schacht (University of Hamburg, DE)

How causal machine learning can leverage marketing strategies: Assessing and improving the performance of a coupon campaign

Henrika Langen (University of Helsinki, FI)

A field experiment on attracting crowdfunders

Lars Hornuf (University of Bremen, Faculty of Business Studies and Economics, DE)

Too casual causality: On the risks of comparing the ITCV to casual benchmarks in management research

Sirio Lonati (NEOMA Business School, FR)

Fair policy learning from observational data

Dennis Frauen (Institute for AI in Management, LMU Munich, DE)

Sophisticated consumers with inertia: Long-term implications from a large-scale field experiment

Klaus Miller (HEC Paris, FR)

Political networking: Consequences for cross-border acquisitions of peer firms

Zhiyan Wu (Erasmus University, NL)

Differences: A package for difference-in-differences with Python

Bernardo Dionisi (Fuqua School of Business, Duke University, US)

Pricing algorithms, nursing homes, and Covid

Ben Tengelsen (IntelyCare, US)

Structural causal modeling of managerial interventions: What if managers had not intervened by doing this?

Gwendolyn Lee (University of Florida, Warrington College of Business, US)

Targeted learning in observational studies with multi-level treatments: an evaluation of antipsychotic drug treatment safety for patients with serious mental illnesses

Jason Poulos (Harvard Medical School, Department of Health Care Policy, US)

Long story short: Omitted variable bias in causal machine learning

Carlos Cinelli (University of Washington, Department of Statistics, US)

Ensure a/b test quality at scale with automated randomization validation and sample ratio mismatch detection

Zhang Zezhong (eBay, US)

Exploiting selection bias on underspecified tasks in large language models

Emily McMilin (Independent Researcher, US)

Keynote

Silvia Chiappa (DeepMind & UCL)