All seminars are on Tuesdays at 8:30 am PT / 11:30 am ET / 4:30 pm London time / 00:30 am(+1day) Beijing time. Please note: Due to recent daylight-saving time changes, the meeting time in your local time zone may have shifted.

Zoom link and other details are provided below. Past talks are available here. Recordings of past webinars are available on our YouTube channel.

Upcoming Seminars

• Tuesday, Jan 13, 2026: Zoom link (webinar ID: 968 8371 7451, password: 414559)  
  - Speaker: Yilin Song (University of Washington) & Richard Guo (University of Michigan)
  - Title: The Categorical Instrumental Variable Model: Characterization, Partial Identification, and Statistical Inference
  - Abstract: We study categorical instrumental variable (IV) models with instrument, treatment, and outcome taking finitely many values. We derive a simple closed-form characterization of the set of joint distributions of potential outcomes that are compatible with a given observed data distribution in terms of a set of inequalities. These inequalities unify several different IV models defined by versions of the independence and exclusion restriction assumptions and are shown to be non-redundant. Finally, given a set of linear functionals of the joint counterfactual distribution, such as pairwise average treatment effects, we construct confidence intervals with simultaneous finite-sample coverage, using a tail bound on the Kullback--Leibler divergence. We illustrate our method using data from the Minneapolis Domestic Violence Experiment.
  - Discussant: Desire Kedagni (University of North Carolina - Chapel Hill)
  [Paper]

• Tuesday, Jan 20, 2025: OCIS+INI joint webinar
  - Speaker: Paul Rosenbaum (University of Pennsylvania)
  - IMPORTANT: This will start at 8 am PT/ 11 am ET/ 4 pm London time/ midnight Beijing time(+1day)
  - Zoom details: Zoom Link, webinar ID: 819 2387 7168​, password: Newton1
  - Title: Being Realistic About Unmeasured Biases in Observational Studies
  - Abstract: Observational studies of the effects caused by treatments are always subject to the concern that an ostensible treatment effect may reflect a bias in treatment assignment, rather than an effect actually caused by the treatment. The degree of legitimate concern is strongly affected by simple decisions that an investigator makes during the design and analysis of an observational study. Poor choices lead to heightened concern; that is, poor choices make a study sensitive to small unmeasured biases where better choices would correctly report insensitivity to larger biases. Indeed, perhaps surprisingly, unambiguous evidence of the presence of unmeasured bias may increase insensitivity to unmeasured bias. These issues are discussed with the aid of some theory and a simple example of an observational study.

• Tuesday, Jan 20, 2025: OCIS+INI joint webinar
  - Speaker: Victor Chernozhukov (MIT)
  - IMPORTANT: This will start at 8 am PT/ 11 am ET/ 4 pm London time/ midnight Beijing time(+1day)
  - Zoom details: Zoom Link, webinar ID: 819 2387 7168​, password: Newton1
  - Title: TBA
  - Abstract: TBA

• Tuesday, Mar 24, 2026: Zoom link (webinar ID: 968 8371 7451, password: 414559)  
  - Speaker: Falco Bargagli Stoffi (University of California, Los Angeles)
  - Title: TBA
  - Abstract: TBA
  - Discussant: TBA

Recordings of our past webinars are available on YouTube. Follow us on YouTube to stay notified!

briel Loewinger, PhD (NIH), Emre Kiciman, PhD (Microsoft), Natalie Levy, PhD (Aetio

Mailing List

To stay up-to-date about upcoming presentations and receive Zoom invitations please join our mailing list. You will receive an email to confirm your subscription. If you are already subscribed to our mailing list and would like to unsubscribe, you may unsubcribe here.

Suggest a speaker

If there is anyone you would like to hear at the Online Causal Inference Seminar, you may let us know here.

Opportunities in Causal Inference

Please check out our opportunities in causal inference page for conferences, workshops, and job listings! If you would like us to list an opportunity, please email us at onlinecausalinferenceseminar@gmail.com.

Youtube channel

Recordings of our past webinars are available on YouTube. Follow us on YouTube to stay notified!

Instructions for Attendees

You can join the webinar by clicking the link on the webpage. If you signed up to the mailing list, you will receive an email with the link before the webinar begins. On Tuesday, you should join the seminar shortly before the start time 8:30 am PT.

Please participate during the seminar!

Due to high demand, we will host the seminar as a Zoom webinar. As an attendee, you will not be able to unmute yourself. If you have questions about the content of the talk, please submit the questions using the Zoom Q&A feature. Time permitting, and depending on the volume of questions, the moderator will either ask your question for you or confirm with you to ask the question yourself and unmute you at a suitable time. In some meetings, the collaborators of the speaker will be online to address your questions in Q&A. Note that Q&A will be moderated by us so you will only be able to see some of the questions of the other attendees. If you want to send messages to the moderators during the seminar, please use the Zoom chat feature. 

Zoom instructions

If you have not used Zoom before, we highly recommend downloading and installing the Zoom client before the meeting. Additional instructions on how to use Zoom during a webinar can be found here. Note that for the online causal inference seminar, we do not require registration in advance so you will be able to join by simply clicking the link on this webpage or in the email.

If you have further questions, please drop us an email at onlinecausalinferenceseminar@gmail.com