Statistical Modeling, Causal Inference, and Social Science: Celebrating Andrew Gelman's 60-ish birthday.
May 29–30, 2026 · Columbia University, New York.
Two-day workshop with invited talks and discussion.
General Info
Venue: The Friday and Saturday workshop sessions will be held at Columbia University, SSW Building, Room C03
1255 Amsterdam Ave, New York, NY 10027
Dinner Banquet: The Friday dinner banquet will be held at the Faculty House, Columbia University.
64 Morningside Dr, New York, NY 10027
Campus access: A QR code will be provided prior to the event for entry to the Columbia campus.
Lodging: We do not have a hotel block; we encourage participants to arrange lodging in advance.
Conference Schedule
Day 1 · May 29 · SSW Bldg · Room C03
8:30 | Breakfast
9:00–9:10 | Opening remarks, Tian Zheng (Columbia)
9:10–9:50 | Extended Talk A: Jennifer Hill (NYU)
Chair: Ben Goodrich (Columbia)
10:00–11:00 | Session 1: The Talented Mr. P
Stephen Ansolabehere (Harvard) TBD, Yajuan Si (Michigan) TBD, Qixuan Chen (Columbia) Predictive Inference for Non-Probability Samples Using Bayesian Machine Learning
Chair: Shigeo Hirano (Columbia)
11:20–12:20 | Session 2: 0.234 — Theory in Computing
Charles Margossian (UBC) TBD, Matt Hoffman TBD, Collin Cademartori (Wake Forest) Can Probabilistic Programming Make Workflows Work?
Chair: Ruobin Gong (Rutgers)
12:20–2:00 | Lunch
2:00–3:00 | Session 3: The Science of Defaults
Susan Gelman (Michigan), Andrew Gelman: The Early Years (and Beyond), Upmanu Lall (Arizona State/Columbia) TBD, Tian Zheng (Columbia) Statistical Thinking and AI Education
Chair: Rahul Dodhia (Microsoft Research)
3:10–4:10 | Session 4: Regression and Other Stories
Jonathan Auerbach (George Mason) How temperature regimes near the equinox synchronize spring biological events?, Rob Trangucci (Oregon State) TBD, David Rothschild (Microsoft Research) Survey Research from MRP to AI: Applying What We Learned from the Last Disruption to Guiding the Next
Chair: Shira Mitchell (Blue Rose Research)
4:20–5:00 | Extended Talk B Sophia Rabe-Hesketh (Berkeley) Simple suggestions for missing data and the DIC
5:00–6:00 | Light refreshments (Faculty House)
6:00–9:30 | Dinner banquet (Faculty House)
Day 2 · May 30 · SSW Bldg · Room C03
8:30 | Breakfast
9:00–9:40 | Extended Talk C Aki Vehtari (Aalto) PSIS-LOO and loo package: 10+ years on
Chair: Charles Margossian
10:00–11:00 | Session 5: The Folk Theorem of Applied Statistics
Yair Ghitza (Catalist) Andrew Gelman's Influence on Real-World Campaigns, Yuling Yao (UT Austin) I cannot believe you have not used MRP in importance weighting, Tom Belin (UCLA) TBD
Chair: Chuanhai Liu (Purdue)
11:20–12:20 | Session 6: The Garden of Forking Paths
Tyler McCormick (University of Washington) Through the Woods and Under the Gate: Navigating the Rashomon Set of Forking Paths, Masanao Yajima (Boston University/Takeda) Walking the Forking Paths Together: A Collaborative Workflow for Robust Inference, Dan Simpson TBD
Chair: Maria Grazia Pittau (Sapienza)
12:20–2:00 | Lunch
2:00–3:00 | Session 7: Panel — 10 Things I (still) Hate About Stan
Daniel Lee (Bayesian Ops), Edward Roualdes (Cal State), Matthijs Vákár (Utrecht), Mitzi Morris (GoldbeltFed), Steve Bronder (Flatiron)
3:20–4:20 | Session 8: Blue Piranha, Red Piranha
Ben Goodrich (Columbia) Table Fusion: Estimating the joint distribution of population characteristics, Sharad Goel (Harvard) Teaching Statistics with AI: A Bag of Tricks, Douglas Rivers (Stanford) The Evidence of Your Eyes and Ears
Chair: Robert S. Erikson (Columbia)
4:30–5:30 | Closing Talk: Four Decades of Bad Ideas, Blind Alleys, Misunderstandings, and Errors
Andrew Gelman (Columbia) Four Decades of Bad Ideas, Blind Alleys, Misunderstandings, and Errors
Introduced by Caroline Gelman (CUNY Hunter College)
