Past Talks and Recordings

The list of past talks (by quarters) with titles, speakers, discussants, and relevant links. Click the subpages to view the same list with abstracts.

Fall 2022

Spring 2022

  • Tuesday, June 28, 2022: Samuel Wang (Cornell University)
    Title:
    Uncertainty Quantification for Causal Discovery
    Discussant: Daniel Malinsky (Columbia University)

    [
    Video] [Slides] [Discussant slides]

  • Tuesday, June 21, 2022: Geneviève Lefebvre (Université du Québec à Montréal)
    Title: Bayesian joint modeling for causal mediation analysis with a binary outcome and a binary mediator
    Discussant: Olli Saarela (University of Toronto)

    [
    Slides] [Discussant slides]

  • Tuesday, June 14, 2022: AmirEmad Ghassami (Johns Hopkins University)
    Title: Combining Experimental and Observational Data for Identification and Estimation of Long-Term Causal Effects
    Discussant: Guido Imbens
    [
    Video] [Slides] [Discussant slides] [Paper]

  • Tuesday, June 7, 2022: Mona Azadkia (ETH)
    Title:
    A Fast Non-parametric Approach for Causal Structure Learning in Polytrees
    Discussant: Bryon Aragam (Chicago Booth)
    [
    Video] [Slides] [Paper]

  • Tuesday, May 31, 2022: Bin Yu (UC Berkeley)
    Title:
    Predictability, stability, and causality with a case study to find genetic drivers of a heart disease
    Discussant: Jas Sekhon (Yale University)

    [
    Slides] [Video]

  • Tuesday, May 17, 2022: Mireille Schnitzer (University of Montreal)
    Title: Estimands and estimation of COVID-19 vaccine effectiveness under the test-negative design: connections to causal inference
    Discussant: David Benkeser (Emory University)
    [
    Slides] [Video]

  • Tuesday, May 10, 2022: Tim Morrison (Stanford University); Harrison Li (Stanford University)
    Talk #1
    : Optimality in multivariate tie-breaker designs
    Talk #2
    : A general characterization of optimal tie-breaker designs
    [
    Video 1] [Video 2] [Speaker 1 slides] [Speaker 2 slides]

  • Tuesday, May 3, 2022: Tyler VanderWeele (Harvard University)
    Title: Causal Inference and Measure Construction: Towards a New Model of Measurement
    Discussant: Fredrik
    Sävje (Yale University)
    [
    Video] [Slides] [Discussant slides]

  • Tuesday, April 26, 2022: Shu Yang (NCSU)
    Test-based integrative analysis for heterogeneous treatment effects combining randomized trial and real-world data
    Discussant: Issa Dahabreh (Harvard University)
    [
    Video] [Slides] [Discussant slides] [Paper]

  • Tuesday, April 19, 202: Alex Luedtke (University of Washington)
    A
    dversarial Monte Carlo Meta-Learning of Conditional Average Treatment Effects
    Discussant: Jonas Metzger (Stanford University)
    [
    Video] [Discussant slides] [Slides]

  • Tuesday, April 12, 2022: Neil Davies (University of Bristol)
    Average causal effect estimation via instrumental variables: the no simultaneous heterogeneity assumption
    Discussant: Eric Tchetgen Techetgen

    [
    Video] [Slides] [Discussant slides] [Paper]

  • Tuesday, April 5, 2022: Zijian Guo (Rutgers University)
    Two Stage Curvature Identification with Machine Learning: Causal Inference with Possibly Invalid Instrumental Variables
    Discussant: Frank Windmeijer (University of Oxford)
    [
    Video] [Slides] [Discussant slides] [Paper]

  • Tuesday, March 29, 2022: Shuangning Li (Stanford University); Michael Oberst (MIT)
    Talk #1:
    Random Graph Asymptotics for Treatment Effect Estimation under Network Interference
    [
    Video] [Slides]
    Talk #2: Regularizing towards Causal Invariance: Linear Models with Proxies
    [Video] [Slides]

  • Tuesday, March 22, 2022: Mathias Drton (Technical University of Munich)
    Half-Trek Criterion for Identifiability of Latent Variable Models
    Discussant: Robin Evans (University of Oxford)

    [
    Video] [Slides] [Discussant slides] [paper]

Winter 2022

  • Tuesday, March 15, 2022: Chengchun Shi (LSE)
    A reinforcement learning framework for dynamic causal effects evaluation in A/B testing
    Discussant: Will Wei Sun (Purdue University)

    [
    Video] [Slides] [Discussant slides]

  • Tuesday, March 8, 2022: Yuansi Chen (Duke University)
    Domain adaptation under structural causal models
    Discussant: Biwei Huang (CMU)

    [
    Video] [Slides] [Discussion slides] [Paper]

  • Tuesday, March 1, 2022: Kosuke Imai (Harvard University)
    Safe Policy Learning through Extrapolation: Application to Pre-trial Risk Assessment

    Discussant: Yifan Cui (National University of Singapore)
    [
    Video] [Slides] [Discussant slides] [Paper]

  • Tuesday, February 22, 2022: Dominik Rothenhäusler (Stanford University)
    Calibrated inference: statistical inference that accounts for both sampling uncertainty and distributional uncertainty
    Discussant: Guido Imbens (Stanford University)

    [
    Video] [Slides]

  • Tuesday, February 15, 2022: Luke Keele (University of Pennsylvania)
    So Many Choices: The Comparative Performance of Statistical Adjustment Methods
    Discussant: Iván Díaz (Cornell University)
    [
    Video] [Slides] [Discussant slides]

  • Tuesday, February 8, 2022: Zhimei Ren (University of Chicago)
    Sensitivity Analysis of Individual Treatment Effects: A Robust Conformal Inference Approach
    Discussant: Stefan Wager (Stanford University)
    [
    Video] [Slides] [Discussant slides] [Paper]

  • Tuesday, February 1 , 2022: Sander Beckers (University of Tübingen)
    Causal Sufficiency and Actual Causation
    Discussant: Thomas Icard (Stanford University)

    [
    Video] [Slides] [Discussant slides] [Paper]

  • Tuesday, January 25, 2022: Daniel McCaffrey (ETS)
    Nonrandom Samples and Causal Inference
    Discussant: Shu Yang (North Carolina State University)

    [
    Video] [Slides] [Discussant slides]

  • Tuesday, January 18, 2022: Sach Mukherjee (University of Cambridge)
    A machine learning approach for causal structure estimation in high dimensions
    Discussant: Yuhao Wang (Tsinghua University)
    [
    Discussant slides]

  • Tuesday, January 11, 2022: Interview with Guido Imbens (Stanford University)
    [
    Video]

Fall 2021

  • Tuesday, December 14, 2021: Ruoxuan Xiong (Emory University)
    Efficient Treatment Effect Estimation in Observational Studies under Heterogeneous Partial Interference
    Discussant:
    Fabrizia Mealli (University of Florence)
    [
    Video] [Slides] [Discussant Slides]

  • Tuesday, December 7, 2021: Jann Spiess (Stanford University)
    Improving Inference from Simple Instruments through Compliance Estimation
    Discussant: Damian Kozbur (University of Zurich)

    [
    Video] [paper] [slides] [Discussant slides]

  • Tuesday, November 30, 2021: Thomas Richardson (University of Washington)
    Single World Intervention Graphs: A simple framework for unifying graphs and potential outcomes with applications to mediation analysis
    Discussant: Mats Stensrud (EPFL)

[Video] [Slides] [Discussant slides]

  • Tuesday, November 16, 2021: Linbo Wang (University of Toronto)
    Causal inference on distribution functions
    Discussant: Hongtu Zhu (
    University of North Carolina at Chapel Hill)
    [
    Paper] [Video] [Slides] [Discussant slides]

  • Tuesday, November 9, 2021: Jin Tian (Iowa State University)
    Estimating Identifiable Causal Effects through Double Machine Learning - Graph-based & Data-driven Approaches
    Discussant: Ilya Shpitser (John Hopkins University)

    [
    Video] [Paper #1, #2] [Slides] [Discussant slides]

  • Tuesday, November 2, 2021: Xinran Li (UIUC)
    Randomization Inference beyond the Sharp Null: Bounded Null Hypotheses and Quantiles of Individual Treatment Effects
    Discussant: Panos Toulis (Chicago Booth)
    [
    Video] [Slides] [Discussant slides]

  • Tuesday, October 26, 2021: Carlos Cinelli (University of Washington)
    Transparent and Robust Causal Inference in the Social and Health Sciences
    Discussant: Guido Imbens (Stanford)
    [
    Video] [Paper #1, #2, #3] [Slides] [Discussant slides]

  • Tuesday, October 19, 2021: Juan Correa (Columbia University & Universidad Autónoma de Manizales) & Nicola Gnecco (University of Geneva)
    Talk1: Generalizing the Effect of Soft Interventions [Video] [Slides]
    Talk2: Causal discovery in heavy-tailed models [Video] [Slides]

  • Tuesday, October 12, 2021: Colin Fogarty (MIT)
    Prepivoting in Finite Population Causal Inference
    Discussant: Tirthanker Dasgupta (Rutgers)

    [
    Video] [Slides] [Discussant slides]

  • Tuesday, October 5, 2021: Eleanor Sanderson (University of Bristol)
    Estimation of causal effects of an exposure at multiple time points through Multivariable Mendelian randomization
    Discussant: Stephen Burgess (University of Cambridge)
    [
    Video] [Slides] [Discussant slides]

  • Tuesday, September 28, 2021: Youjin Lee (Brown University)
    Evidence factors from multiple, possibly invalid, instrumental variables
    Discussant: Jose
    Zubizarreta (Harvard University)
    [
    Video] [Slides] [Discussant slides]

  • Tuesday, September 21, 2021: Ted Westling (University of Massachusetts, Amherst)
    Nonparametric tests of the causal null with non-discrete exposures
    Discussant:
    Oliver Dukes (University of Pennsylvania)
    [
    Video] [Paper] [Slides] [Discussant slides]

  • Tuesday, September 14, 2021: Daniel Malinsky (Columbia University)
    Explaining the Behavior of Black-Box Prediction Algorithms with Causal Learning
    Discussant: Joshua Loftus (LSE
    )
    [
    Video] [Paper] [Slides] [Discussant slides]

  • Tuesday, September 7, 2021: Joseph Antonelli (University of Florida)
    Heterogeneous causal effects of neighborhood policing in New York City with staggered adoption of the policy
    Discussant: Matthew Cefalu (RAND Corporation)

    [
    Video] [Paper] [Slides]

  • Tuesday, August 31, 2021: Susan Athey and Stefan Wager (Stanford)
    Estimating heterogeneous treatment effects in R
    [
    Video] [Athey Slides] [Wager Slides]

Summer 2021

  • Tuesday, August 10, 2021: Maggie Makar (University of Michigan); Xiaojie Mao (Tsinghua University)
    Talk #1:
    Causally motivated shortcut removal using auxiliary labels (Maggie Makar)
    [
    Video] [Slides]
    Talk #2:
    Controlling for Unmeasured Confounding in Panel Data Using Minimal Bridge Functions: From Two-Way Fixed Effects to Factor Models (Xiaojie Mao)
    [
    Video] [Paper] [Slides]

  • Tuesday, August 3, 2021: Anish Agarwal (MIT) and Dennis Shen (Berkeley)
    Synthetic Interventions
    Discussant: Jason Poulos (Harvard)
    [
    Video] [Paper] [Slides] [Discussant slides]

  • Tuesday, July 27, 2021: Johannes Textor (Radboud University)
    Causal Inference using the R package DAGitty
    [
    Video] [Slides]

  • Tuesday, July 20, 2021: Fiammetta Menchetti (Universita degli Studi di Firenzi); Armeen Taeb (ETH Zürich)
    Talk 1:
    Estimating the causal effect of an intervention in a time series setting: the C-ARIMA approach (Fiammetta Menchetti)
    [
    Video] [Slides]
    Talk 2:
    Perturbations and causality in Gaussian latent variable models (Armeen Teb)
    [Video] [Slides]

  • Tuesday, July 13, 2021: Alexander Volfovsky (Duke University)
    Online experimentation for studying political polarization
    Discussant: Edo Airoldi (Temple University)
    [Video] [Paper #1] [Paper #2] [Slides] [Discussant slides]

  • Tuesday, July 6, 2021: Isaiah Andrews (Harvard University)
    Inference on Winners
    Discussant: Will Fithian (UC Berkeley)
    [
    Video] [Paper] [Slides] [Discussant slides]

  • Tuesday, June 29, 2021: Sam Pimentel (UC Berkeley)
    Optimal tradeoffs in matched designs comparing US-trained and internationally-trained surgeons.
    Discussant: Magdalena Bennett (UT Austin)
    [
    Video] [Paper] [Slides]

  • Tuesday, June 22, 2021: Stefan Wager (Stanford University)
    Treatment Effects in Market Equilibrium (joint work with Evan Munro and Kuang Xu)
    Discussant: Fredrik Sävje (Yale University)
    [
    Video] [Slides] [Discussant slides]

  • Tuesday, June 15, 2021: Guido Imbens (Stanford University)
    Using Experiments to Correct for Selection in Observational Studies
    Discussant: Nathan Kallus (Cornell University)
    [
    Video] [Slides] [Discussant slides]

Spring 2021

  • Tuesday, June 8, 2021: Leon Bottou (Facebook)
    Learning Representations Using Causal Invariance
    Discussant: Dominik Rothenhäusler (Stanford University)
    [
    Video]

  • Tuesday, June 1, 2021: Niklas Pfister (University of Copenhagen)
    Statistical Testing under Distributional Shifts
    Discussant: Thomas Berrett (University of Warwick)

    [
    Video] [Paper] [Slides]

  • Tuesday, May 25, 2021: Razieh Nabi (Johns Hopkins University)
    Semiparametric inference for causal effects in graphical models with hidden variables
    Discussant: Eric Tchetgen Tchetgen (University of Pennsylvania)

    [
    Video] [Slides] [Discussant slides]

  • Tuesday, May 18, 2021: Speaker: Ramesh Johari (Stanford University)
    Experimental design in two-sided platforms: an analysis of bias
    Discussant: Panos Toulis (University of Chicago)

    [
    Video] [Paper] [Slides] [Discussant slides]

  • Tuesday, May 11, 2021: Corwin Zigler (University of Texas at Austin)
    Bipartite inference and air pollution transport: estimating health effects of power plant interventions
    Discussant: Forrest Crawford (Yale)
    [
    Video] [Paper] [Slides]

  • Tuesday, May 4, 2021: Sara Magliacane (University of Amsterdam, MIT-IBM Watson AI Lab)
    Domain adaptation by using causal inference to predict invariant conditional distributions
    Discussant: Dominik Rothenhäusler (Stanford University)
    [
    Video] [Paper] [Slides] [Discussant slides]

  • Tuesday, April 27, 2021: Issa Dahabreh (Harvard University)
    Causally interpretable meta-analysis: transporting inferences from multiple randomized trials to a target population
    Discussant: Eloise Kaizar (The Ohio State University)

    [
    Slides] [Discussant slides]

  • Tuesday, April 20, 2021: Alberto Abadie (MIT)
    A Penalized Synthetic Control Estimator for Disaggregated Data
    Discussant: Stefan Wager (Stanford)
    [
    Video] [Paper] [Slides]

  • Tuesday, April 13, 2021: Andrea Rotnitzky (Di Tella University, Buenos Aires)
    Optimal adjustment sets in non-parametric graphical models
    Discussant:
    Ema Perkovic (University of Washington)
    [
    Video] [Slides] [Discussant slides]

  • Tuesday, April 6, 2021: Richard Berk (University of Pennsylvania)
    Firearm Sales in California Through the Myopic Vision of an Interrupted Time Series Causal Analysis
    Discus
    sant: John Donohue (Stanford)
    [
    Video] [Slides] [Discussant slides]

  • Tuesday, March 30, 2021: Elizabeth Stuart (Johns Hopkins University)
    Using stacked comparative interrupted time series to estimate opioid policy effects
    Discussant: Laura Hatfield (Harvard)
    [
    Slides]

Winter 2021

  • Tuesday, March 23, 2021: Joshua Angrist (MIT)
    Simple and Credible Value-Added Estimation Using Centralized School Assignment
    Discussant: Jesse Rothstein (UC Berkeley)

    Joint with Peter Hull, Parag Pathak, Christopher Walters
    [
    Paper] [Slides] [Discussant slides]

  • Tuesday, March 16, 2021: Kun Zhang (Carnegie Mellon)
    "
    Learning and Using Causal Representations"
    Discussant: C
    osma Shalizi (Carnegie Mellon)
    [
    Video] [Slides] [Discussant slides]

  • Tuesday, March 9, 2021: Luke Keele (University of Pennsylvania)
    "Hospital Quality Risk Standardization via Approximate Balancing Weights"
    Discussant: Sam Pimentel (UC Berkeley)
    [
    Video] [Paper] [Slides] [Discussant slides]

  • Tuesday, March 2, 2021: Fredrik Sävje (Yale)
    "
    Balancing covariates in randomized experiments using the Gram-Schmidt Walk"
    Discussant
    : Peng Ding (UC Berkeley)
    [Video] [Slides] [Paper] [Discussant slides]

  • Tuesday, February 23, 2021: Fan Li (Duke University)
    "Causal Mediation Analysis for Sparse and Irregular Longitudinal Data"
    Discussant:
    Georgia Papadogeorgou (University of Florida)
    [
    Video] [Slides] [Discussant slides]

  • Tuesday, February 16, 2021: Donald Green (Columbia University)
    "Using Placebo-Controlled Designs to Detect Edutainment Effects and Spillovers: Results from Two Large-Scale Experiments in Uganda"
    Discussant: Molly Offer-Westort (Stanford)
    [
    Video] [Paper] [Slides] [Discussant slides]

  • Tuesday, February 9, 2021: Martin Tingley and Jeffrey Wong (Netflix)
    "Supporting Innovation and Scale with a Democratized Experimentation Platform"
    Discussant: Iavor Bojinov (Harvard)

  • Tuesday, February 2, 2021: Interview with James Robins (Harvard)
    [Video]

  • Tuesday, January 26, 2021: Stephen Bates (UC Berkeley)
    "
    Causal Inference in Genetic Trio studies"
    Discussant:
    Qingyuan Zhao (University of Cambridge)
    [
    Video] [Slides] [Discussant slides] [Paper]

  • Tuesday, January 19, 2021: Mark van der Laan (UC Berkeley)
    "Higher order Targeted Maximum Likelihood Estimation"
    Discussant: Alex
    Luedtke (University of Washington)
    [
    Video] [Slides] [Discussant slides]

  • Tuesday, January 12, 2021: Susan Athey (Stanford GSB)
    "Synthetic Difference in Differences" (with Dmitry Arkhangelsky, David A. Hirshberg, Guido Imbens, Stefan Wager)
    [
    Video] [Slides] [Paper]

Fall 2020

  • Tuesday, December 15, 2020: Luke Miratrix (Harvard)
    "Using national data and meta-analysis techniques to get a handle on how bad some biases might be in practice"
    Discussant: Elizabeth Tipton (Northwestern University)
    [Video] [Slides]

  • Tuesday, December 8, 2020: Qingyuan Zhao (University of Cambridge)
    "Selection bias in 2020"
    Discussant: Louisa Smith (Harvard University)
    [
    Video] [Slides] [Discussant slides]

  • Tuesday, December 1, 2020: Vanessa Didelez (University of Bremen)
    "Causal reasoning in survival and time-to-event analyses"
    Discussant: Els Goetghebeur (Ghent University)
    [Video] [Slides] [Paper 1] [Paper 2] [Paper 3] [Paper 4]

  • Tuesday, November 24, 2020: Fan Li (Yale)
    "Propensity score weighting for covariate adjustment in randomized clinical trials"
    Discussant: Kari Lock Morgan (Penn State University)
    [Video] [Paper] [Slides] [Discussant slides]

  • Tuesday, November 17, 2020: Interview with Judea Pearl (UCLA)
    [Video]

  • Tuesday, November 10, 2020: Dean Knox (Wharton) (with Justin Grimmer (Stanford) and Brandon Stewart (Princeton))
    "Naïve regression requires weaker assumptions than factor models to adjust for multiple cause confounding"
    Discussants: Betsy Ogburn (Johns Hopkins) (with Ilya Shpitser (Johns Hopkins) and Eric Tchetgen Tchetgen (Wharton))
    [Video] [Paper] [Slides] [Discussant slides]

  • Tuesday, November 3, 2020: Interview with Donald Rubin (Harvard)
    [Video]

  • Tuesday, October 27, 2020: David Blei (Columbia University)
    "The Deconfounder: What is it? What is its theory? Is it useful?"
    Discussant: Guido Imbens (Stanford)
    [Video] [Paper] [Speaker slides] [Discussant slides]

  • Tuesday, October 20, 2020: Ismael Mourifie (University of Toronto)
    "Testing Identification assumptions in Fuzzy Regression Discontinuity Designs"
    Discussant:
    Zhuan Pei (Cornell)
    [Video] [Paper (supplement)] [Speaker slides] [Discussant slides]

  • Monday, October 12, 2020: Interview with Esther Duflo (MIT)
    [Video]

  • Tuesday, October 7, 2020: Peng Ding (UC Berkeley)
    "Randomization and Regression Adjustment"
    Discussant: Tirthankar DasGupta (Rutgers)
    [Video] [Paper] [Speaker slides] [Discussant slides]

  • Tuesday, September 29, 2020: Emilija Perkovic (University of Washington)
    "Causal effects in maximally oriented partially directed acyclic graphs (MPDAGs): Identification and efficient estimation"
    Discussant:
    Thomas Richardson (University of Washington)
    [Video] [Paper 1] [Paper 2] [Speaker slides] [Discussant slides]

  • Tuesday, September 23, 2020: Falco Bargagli Stoffi (Harvard); Eli Ben-Michael (UC Berkeley)
    Talk 1: "Causal Rule Ensemble: Interpretable Inference of Heterogeneous Treatment Effects" (Falco Bargagli Stoffi)
    Talk 2: "Synthetic Controls with Staggered Adoption" (Eli Ben-Michael)
    [
    Video] [Bargagli Stoffi slides] [Ben-Michael slides]

  • Tuesday, September 15, 2020: Nathan Kallus and Xiaojie Mao (Cornell University)
    "Localized Debiased Machine Learning: Efficient Inference on Quantile Treatment Effects and Beyond"
    Discussant: Alexandre Belloni (Duke)
    [
    Video] [Paper] [Speaker slides]

  • Tuesday, September 8, 2020: Joris Mooij (University of Amsterdam)
    "Joint Causal Inference: A Unifying Perspective on Causal Discovery"
    Discussant: Philip Dawid (University of Cambridge)
    [Video] [Paper] [Speaker slides] [Discussant slides]

  • Tuesday, September 2, 2020: Karthika Mohan (Berkeley); David Hirshberg (Stanford)
    Talk 1: "Causal Graphical Models for Handling Missing Data" (Karthika Mohan)
    Talk 2
    : "Balance in Causal Inference: From Poststratification to Regularized Riesz Representers" (David Hirshberg)
    [
    Hirshberg video] [Hirshberg slides]

Summer 2020

  • Tuesday, August 25, 2020: Cynthia Rudin, Alexander Volfovsky, Sudeepa Roy (Duke)
    "Almost Matching Exactly"
    Discussant: Guillaume Basse (Stanford)
    [Video] [Almost Matching Exactly Website] [Speaker slides] [Discussant slides]

  • Tuesday, August 18, 2020: Judith Lok (Boston University)
    "Causal organic indirect and direct effects: closer to Baron and Kenny, with a product method for binary mediators"
    Discussant: Kosuke Imai (Harvard University)
    [Video] [Paper] [Speaker slides] [Discussant slides]

  • Tuesday, August 11, 2020: Panos Toulis (Chicago Booth)
    "Randomization tests for spillovers under general interference: A graph-theoretic approach"
    Discussant: Peng Ding (Berkeley)
    [Video] [Paper] [Speaker slides] [Discussant slides]

  • Tuesday, August 4, 2020: Andrew Gelman (Columbia University)
    "100 Stories of Causal Inference"
    [
    Video] [Paper]

  • Tuesday, July 28, 2020: Georgia Papadogeorgou (University of Florida) and Lihua Lei (Stanford University)
    Talk 1: "Causal inference with spatio-temporal data: estimating the effects of airstrikes on insurgent violence in Iraq" (Georgia Papadogeorgou)
    Talk 2: "Conformal Inference of Counterfactuals and Individual Treatment Effects" (Lihua Lei)
    [
    Video] [Papdogeorgou slides] [Lei slides] [Lei Paper] [Papadogeorgou Paper]

  • Tuesday, July 21, 2020: Yiqing Xu (Stanford) and Xun Pang (Tsinghua University)
    "A Bayesian Alternative to Synthetic Control for Comparative Case Studies: A Dynamic Multilevel Latent Factor Model with Hierarchical Shrinkage"
    Discussant: Dmitry Arkhangelsky (CEMFI, Madrid)
    [Video] [Paper] [Speaker slides] [Discussant slides]

  • Tuesday, July 14, 2020: Michal Kolesár (Princeton)
    "Finite-Sample Optimal Estimation and Inference on Average Treatment Effects Under Unconfoundedness"
    Discussant: Luke Miratrix (Harvard)
    [Video] [Paper] [Speaker slides] [Discussant Slides]

  • Tuesday, July 7, 2020: Caroline Uhler (MIT)
    "Causal Inference in the Light of Drug Repurposing for SARS-CoV-2"
    [
    Video] [Speaker slides]

  • Tuesday, June 30, 2020: Marloes Maathuis (ETH Zürich)
    "Total causal effect estimation by combining causal structure learning and covariate adjustment"
    Discussant: Daniel Malinsky (Columbia)
    [
    Video] [Paper 1] [Paper 2] [Paper 3] [Paper 4 (supplement)] [Paper 5] [Speaker slides] [Discussant slides]

  • Tuesday, June 23, 2020: Eytan Bakshy (Facebook)
    "Efficient Experimentation and Inference for Large Decision Spaces"
    Discussant: Dean Eckles (MIT)
    [
    Video] [Speaker slides] [Discussant Slides]

  • Tuesday, June 16, 2020: Jonas Peters (University of Copenhagen)
    "Causality and distribution generalization"
    Discussant: Yuansi Chen (ETH Zürich)
    [Video] [Main paper] [Paper 1] [Paper 2] [Paper 3] [Speaker slides] [Discussant slides]

  • Tuesday, June 9, 2020: Dean Eckles (MIT)
    "Noise induced randomization in regression discontinuity designs"
    Discussant: Michal Kolesár (Princeton)
    [
    Video] [Speaker slides]

  • Tuesday, June 2, 2020: Paul Rosenbaum (Wharton)
    "Replication and Evidence Factors in Observational Studies"
    [
    Video] [Handout] [Speaker slides]

Spring 2020

  • Tuesday, May 26, 2020: Ya Xu (LinkedIn)
    "Causal Inference Challenges in Industry: A perspective from experiences at LinkedIn"
    Discussant: Iavor Bojinov (Harvard)
    Abstract: In this talk, we will briefly give some background how online controlled experiments are commonly used in industry, and introduce some challenges we face, and also some opportunities in novel applications.
    [
    Video] [Speaker slides] [Discussant slides]

  • Tuesday, May 19, 2020: Susan Murphy (Harvard University)
    "Inference for Batched Bandits"
    Discussant: Stefan Wager (Stanford University)
    [
    Video] [Paper] [Speaker slides] [Discussant slides]

  • Tuesday, May 12, 2020: Ilya Shpitser (Johns Hopkins University)
    "Identification and estimation in graphical models of missing data"
    Discussant: Jin Tian (Iowa State University)
    [
    Video] [Paper 1] [Paper 2] [Paper 3] [Speaker slides]

  • Tuesday, May 5, 2020: Eric Tchetgen Tchetgen (Wharton)
    "Selective Machine Learning of Doubly Robust Functionals"
    Discussant: Stijn Vansteelandt (UGent)
    [
    Video] [Paper] [Speaker slides]

  • Tuesday, April 28, 2020: Edward Kennedy (Carnegie Mellon University)
    "Optimal doubly robust estimation of heterogeneous causal effects"
    Discussant: James Robins (Harvard University)
    [
    Video] [Paper] [Speaker slides]

  • Tuesday, April 21, 2020: Elizabeth Ogburn (Johns Hopkins University)
    "Social network dependence, unmeasured confounding, and the replication crisis"
    Discussant: Ilya Shpitser (Johns Hopkins University)
    [Video] [Paper] [Speaker slides]

  • Tuesday, April 14, 2020: Elizabeth Tipton (Northwestern University)
    "Will this Intervention Work in this Population? Designing Randomized Trials for Generalization"
    Discussant: Andrew Gelman (Columbia University)
    [Video] [Website: The Generalizer] [Paper] [Speaker slides]

  • Tuesday, April 8, 2020: Hyunseung Kang (University of Wisconsin-Madison)
    "Inferring Treatment Effects After Testing Instrument Strength in Linear Models" (w/ Nan Bi and Jonathan Taylor)
    Discussant: Will Fithian (UC Berkeley)
    [
    Video] [Paper] [Speaker slides]

  • Tuesday, March 31, 2020: Dylan Small (Wharton)
    "Testing an Elaborate Theory of a Causal Hypothesis" (w/ Bikram Karmakar)
    Discussant: Peter Bühlmann (ETH Zurich)
    [Video] [Paper] [Speaker slides]