With PhD students, postdocs, and associated researchers, we organize weekly seminars - currently only online. In this weekly group meeting, we alternate presentations by invited researchers on the topics of missing data, causal inference but also ML/statistics in general, with presentations by students of the group and also paper reading sessions.

Here you can find a list of group meetings with abstracts. We regularly update the links and list of confirmed speakers. Please contact Bénédicte Colnet or Pan Zhao if you are interested to get the slides or if you want to visit us or to receive the announcement for the talks.

See below the calendar for more details.

Group Meeting

  • 2022-11-30, Xiao Wu, Postdoc at Stanford University, USA: Assessing the causal effects of a stochastic intervention in time series data.

  • 2022-11-29, Yiye Jiang, PhD student at Institut de Mathématiques de Bordeaux, France: Graph learning with autoregressive models for complex data types.

  • 2022-11-21, Aude Sportisse, Postdoc at 3iA Côte d’Azur, France: Informative labels in Semi-Supervised Learning.

  • 2022-11-16, Marco Carone, Associate Professor of Biostatistics at University of Washington, USA: Inference for algorithm-agnostic variable importance.

  • 2022-11-02, Curtis Northcutt, CEO & Co-Founder of Cleanlab, USA: Cleanlab: Automatically Find and Fix Errors in ML Datasets.

  • 2022-10-26, Ruishan Liu, Postdoc at Stanford, USA: AI for clinical trials design.

  • 2022-10-18, Arthur Gretton, Professor at University College London, UK: Deep Causal Inference.

  • 2022-10-14, Matthieu Marbac-Lourdelle, Assistant Professor at ENSAI/CREST, France: Model selection for non-parametric mixtures and hidden Markov models.

  • 2022-09-27, Elizabeth Stuart, Professor at Johns Hopkins University, USA: Combining experimental and population data to estimate population treatment effects.

  • 2022-09-14, Mary Beth Nebel, Assistant Professor of Neurology at Johns Hopkins University, USA: Accounting for motion in fMRI: What part of the spectrum are we characterizing in autism spectrum disorder?

  • 2022-07-06, Romain Pirracchio, Professor at University of California San Francisco, USA: Heterogeneous Treatment Effect in medicine: convergence between ML and Causal Inference.

  • 2022-06-29, François Husson, Professor at Agrocampus Ouest, France: Visualisation de données multi-tableaux par analyse factorielle multiple.

  • 2022-06-15, Alexandre Perez, PhD Student at SoDa team, Inria, France: Beyond calibration: estimating the grouping loss of modern neural networks.

  • 2022-06-10, Eric Laber, Professor of Statistical Science at Duke University, USA: Safe Contextual Bandits in mHealth.

  • 2022-06-07, Sofia Triantafyllou, Assistant Professor at University of Crete, Greece: Causal effect estimation using observational and experimental data.

  • 2022-06-03, Michael Elliott, Professor of Biostatistics at the University of Michigan, USA: Using Synergies Between Survey Statistics and Causal Inference to Improve Transportability of Clinical Trials.

  • 2022-05-30, Sylvain Sardy, Associate Professor at University of Geneva, Switzerland: A phase transition for finding needles in nonlinear haystacks with LASSO artificial neural networks.

  • 2022-05-18, Chris Harschaw, Postdoctoral Scholar at Simons Institute, USA: Interference in Randomized Experiments: Survey and Challenges.

  • 2022-05-16, Jeffrey Näf and Meta Lina Spohn, PhD students at ETH Zürich, Switzerland: Imputation Scores: How to choose an imputation method?

  • 2022-05-11, Erica Moodie, Professor of Biostatistics at McGill University, Canada: Regression-Based Methods To Estimate Adaptive Treatment Strategies.

  • 2022-04-27, Nathan Kallus, Assistant Professor at Cornell University and Cornell Tech, USA: Smooth Contextual Bandits.

  • 2022-03-30, Felipe Tobar, Associate Professor at the Universidad de Chile, Chile: Gaussian processes, missing data, and optimal transport.

  • 2022-03-14, Jiwei Zhao, Assistant Professor at the University of Wisconsin–Madison, USA: A Journey of Understanding Nonignorable Missingness and Some Reflections.

  • 2022-02-16, Fredrik Johansson, Assistant Professor at Chalmers University of Technology, Sweden: Generalization Bounds for Estimation of Causal Effects.

  • 2022-02-14, Celestine Mendler-Dünner, Research Group Lead at the Max Planck Institute for Intelligent Systems in Tübingen, Germany: Performative Prediction.

  • 2022-01-26, Torsten Hothorn, Professor at the University of Zürich, Switzerland: Transformation Models: Pushing the Boundaries.

  • 2022-01-17, Robin Genuer, Associate professor at ISPED, Université de Bordeaux, France: Fréchet random forests for metric space valued regression with non euclidean predictors.

  • 2022-01-12, David Haziza, Professor at the University of Ottawa, Canada: Efficient multiply robust imputation in the presence of influential units in surveys.

  • 2022-01-10, Ioanna Manolopoulou, Associate Professor at University College London, UK: Bayesian Causal Forests for Heterogeneous Treatment Effects Estimation from randomized and observational data.

  • 2022-01-05, Clément Bénard, Research Engineer in Machine Learning & Statistics at Safran, France: Variable importance for random forests: MDA and Shapley effects.


Reading Groups

  • Introduction to causal inference for statisticians

  • Targeted learning


We also organize common group meetings with Gaël Varoquaux’s Inria team. For more information about these group meetings, contact Bénédicte Colnet.

Members of our group follow different seminars and events, a selection is given in the google calendar. Additionally, we keep a list of conferences and summer schools that some of us potentially plan to attend here.