Activities & Events

The PCI Lab hosts a causal learning group consisting of students and faculty from diverse disciplines including statistics, epidemiology, political science, sociology, computer science, and more. Meetings are typically held on Fridays from 11:00 am – 12:15 pm PST. If you are interested in joining us, click here to be added to our email distribution list.

Additionally, you can find a listing of past and upcoming events
below.

Date Title Presenters
November 21 2025 Causal Inference, Data Integration, Small and Large Data, and Scalable Estimation Michele Santacatterina
November 14 2025 Measurement Error Corrections Using Control Variates (with Applications to Children's Health) Kevin Josey
November 7 2025 Causally Selected Covariates for Regression Calibration Wenze Tang
October 31 2025 Causal Inference in the Context of PAC Contributions & School Shootings Takuma Iwasaki , Eric Baldwin
October 24 2025 On the Structural Basis of Conditional Ignorability Drago Plecko
October 17 2025 Reliable and Effective Data Fusion Sijia Li
October 10 2025 Average Direct and Indirect Causal Effects of Persuasion Wenlu Xu
June 6 2025 Heterogeneous treatment effects (co-hosted with UCLA IDS Lab) Duy Pham, Roch Nianogo, Jiahui Xu
May 30 2025 Selection bias and missing data Maya Mathur
May 23 2025 Innovations in causal inference methods Chad Hazlett, Borna Bateni
May 9 2025 Mendelian Randomization & time-varying exposures Joy Shi
April 25 2025 Mendelian Randomization Sonja Swanson
April 18 2025 Causal estimands for survival analysis L. Paloma Rojas-Saunero
April 11 2025 Applications of Bayesian nonparametrics in causal inference Falco J. Bargagli-Stoffi
March 7 2025 What is Causal Reasoning Judea Pearl
February 28 2025 Post-treatment problems: What can we say about the effect of a treatment among sub-groups who (would) respond in some way? Tanvi Shinkre, Matthew Coates, Chad Hazlett
February 14 2025 Principal stratification Kirk Vanacore
February 7 2025 How COVID ruined the test-negative design for estimating influenza vaccine effectiveness Sheena Sullivan
January 31 2025 Causal inference applications to firearm policy Jack Kappelman, Haotian Chen, Falco J. Bargagli-Stoffi
January 17 2025 Causal inference applications to PTSD and glioblastoma therapies Chad Hazlett
November 22 2024 Immortal time bias Matthew Coates
November 15 2024 Heterogeneous effects of Medicaid coverage on cardiovascular risk factors Kosuke Inoue
November 8 2024 DAGs and effect heterogeneity Onyebuchi Arah
November 1 2024 Beyond Prediction: Identifying Latent Treatments in Images Michelle Torres
October 25 2024 Danish National Birth Cohort (DNBC) Cecilia H. Ramlau-Hansen
October 18 2024 Front-Door Formula Onyebuchi Arah
May 31 2024 Gaussian processes for extrapolative inference -- a powerful tool for addressing model-dependency and uncertainty Chad Hazlett, Doeun Kim, Soonhong Cho
May 24 2024 Causal progress with imperfect placebo treatments and outcomes Adam Rohde
May 10 2024 Regression-based proximal causal inference Eric J. Tchetgen Tchetgen
May 3 2024 Safe learning outside of randomized trials: Application of the stability-controlled quasi-experiment to the effects of three COVID-19 therapies (with Wulf, Hill, Chiang, Goodman-Meza, Pasaniuc, Arah, Erlandson & Montague) Chad Hazlett, Onyebuchi Arah, David Ami Wulf
April 16 2024 Detecting and refuting monotonicity Scott Mueller
February 16 2024 Analyzing the impact of events through surveys: Formalizing biases and introducing the dual randomized survey design Andrew Bertoli
February 9 2024 Double robust, flexible adjustment methods for causal inference: An overview and an evaluation Nathan Hoffmann
February 2 2024 Causal estimands when competing events are present L. Paloma Rojas-Saunero
January 16 2024 Understanding regression’s “weighting problem” and its simple, longstanding, equivalent fixes Tanvi Shinkre