Conferences / StanCon
StanCon 2026 Uppsala
Aug 17–21, 2026 · Uppsala University (English Park; Ångström Laboratory), Uppsala, Sweden
- Conference
- StanCon Data science & ML
- Dates
- Aug 17, 2026 – Aug 21, 2026
- Venue
- Uppsala University (English Park; Ångström Laboratory)
- Place
- Uppsala, Sweden
- Format
- In person
- Status
- Past
- Attendance
- —
- Website
- stancon2026.org
- Recorded
- 4 sponsors · 58 speaker appearances
- Notes
- International Conference on Bayesian Inference and Probabilistic Programming. Tutorials Aug 17, talks Aug 18-21. Keynotes/tutorials from the talks archive; contributed talks parsed from the PDF schedule (flash talks/posters not included).
Ticket prices
No ticket prices recorded
Sponsors 4
Other 4
- Beijerstiftelsen · Sponsor
- Carl Tryggers Stiftelse · Sponsor
- Essence · Sponsor
- SweCSS · Sponsor
Speakers and talks 58
| Speaker | Company | Role | Talk | Links |
|---|---|---|---|---|
| Anna Dreber | — | Keynote | (Predicting) replications and generalizability of (mainly experimental) social science results | — |
| Fredrik Ronquist | — | Keynote | Universal probabilistic programming for phylogenetics: challenges and opportunities | — |
| Kaitlyn Johnson | — | Keynote | Joint modelling to infer transmission and evolutionary dynamics of infectious diseases from multiple different data sources | — |
| Matthew Kay | — | Keynote | Systematic uncertainty visualization design (and its foundation in probabilistic models) | — |
| Adrian Seyboldt | — | Speaker | From Mass Matrix Adaptation to Normalizing Flows | — |
| Aki Vehtari | — | Workshop | Contributing to Stan: A Developer’s Guide to the Core, Interfaces, and First Contributions | — |
| Aki Vehtari | — | Speaker | Embedded Laplace Approximation in Stan | — |
| Aki Vehtari | — | Speaker | To select or not to select - predictively consistent priors instead of model selection | — |
| Aleksi Lahtinen | — | Speaker | Probabilistic Ordinal Regression for Hierarchical Survey Data | — |
| Alexandre Andorra | — | Speaker | Stan Live session , Ångström Laboratory | — |
| Anna Elisabeth Riha | — | Speaker | To select or not to select - predictively consistent priors instead of model selection | — |
| Bob Carpenter | — | Speaker | Within-orbit adaptive leapfrog sampler (WALNUTS) with continuous Nutpie adaptation | — |
| Brian Ward | — | Workshop | Contributing to Stan: A Developer’s Guide to the Core, Interfaces, and First Contributions | — |
| Brian Ward | — | Speaker | Embedded Laplace Approximation in Stan | — |
| Brian Ward | — | Speaker | Understanding Stan so you can write JAX | — |
| Charles Margossian | — | Speaker | Embedded Laplace Approximation in Stan | — |
| collin cademartori | — | Speaker | variance deltas: interactive visualizations for explaining bayesian uncertainty | — |
| David Kohns | — | Speaker | To select or not to select - predictively consistent priors instead of model selection | — |
| Fabian Jirasek | — | Speaker | Probabilistic Matrix Completion for Chemical Engineering Applications | — |
| Florence Bockting | — | Workshop | Contributing to Stan: A Developer’s Guide to the Core, Interfaces, and First Contributions | — |
| Hans Hasse | — | Speaker | Probabilistic Matrix Completion for Chemical Engineering Applications | — |
| Jakob Torgander | — | Speaker | simplexmcmc: an auxiliary-variable framework for mixed continuous-discrete posterior distributions | — |
| Jan Glaubitz | — | Workshop | Bayesian Inference for Sparsity-Promoting and Edge-Preserving Priors in Probabilistic Programming | — |
| Javier Enrique Aguilar | — | Speaker | Intuitive R2 based prior specification for high-dimensional models | — |
| Javier Enrique Aguilar | — | Speaker | Latent variable estimation with composite Hilbert space Gaussian processes | — |
| John Ashley Burgoyne | — | Speaker | Incorporating Response Times into Item Response Models: A Case Study with Special Functions in Stan | — |
| Jonas Wallin | — | Speaker | Hierarchical Riemannian manifold Hamiltonian Monte Carlo algorithms | — |
| Jonas Wallin | — | Speaker | simplexmcmc: an auxiliary-variable framework for mixed continuous-discrete posterior distributions | — |
| Julie Bertrand | — | Workshop | Stan for pharmacometrics | — |
| Lassi Roininen | — | Workshop | Bayesian Inference for Sparsity-Promoting and Edge-Preserving Priors in Probabilistic Programming | — |
| Leevi Lindgren | — | Speaker | To select or not to select - predictively consistent priors instead of model selection | — |
| Leo Lahti | — | Speaker | Probabilistic Ordinal Regression for Hierarchical Survey Data | — |
| Leo Lahti | — | Speaker | An Introduction to Probabilistic Data Analysis with Stan on the Carpentries Platform | — |
| Luna Fazio | — | Speaker | Bayesian Distributional Structural Equation Modeling in Stan | — |
| Manfred Claassen | — | Speaker | Latent variable estimation with composite Hilbert space Gaussian processes | — |
| Måns Magnusson | — | Speaker | simplexmcmc: an auxiliary-variable framework for mixed continuous-discrete posterior distributions | — |
| Marcello Zago | — | Speaker | Latent variable estimation with composite Hilbert space Gaussian processes | — |
| Mitzi Morris | — | Workshop | An introduction to applied Bayesian statistics with Stan | — |
| Nathanael Hoze | — | Workshop | Stan for pharmacometrics | — |
| Nicolas Hayer | — | Speaker | Probabilistic Matrix Completion for Chemical Engineering Applications | — |
| Nikolai Vetr | — | Speaker | Population Effect Estimation in Bayesian Hierarchical Models using Sum-to-Zero Constraints | — |
| Nikolas Siccha | — | Speaker | StanBlocks.jl: a Julia-based frontend for writing and composing Stan models | — |
| Nils Rudi | — | Speaker | Luck, skill, and the battle of the sexes: analyzing tennis | — |
| Noa Kallioinen | — | Workshop | Bayesian model diagnostics: Workflows and software tools | — |
| Osvaldo Martin | — | Workshop | Bayesian model diagnostics: Workflows and software tools | — |
| Paul Goldsmith-Pinkham | — | Speaker | Luck, skill, and the battle of the sexes: analyzing tennis | — |
| Paul-Christian Bürkner | — | Speaker | Bayesian Distributional Structural Equation Modeling in Stan | — |
| Paul-Christian Bürkner | — | Speaker | Intuitive R2 based prior specification for high-dimensional models | — |
| Paul-Christian Bürkner | — | Speaker | Latent variable estimation with composite Hilbert space Gaussian processes | — |
| Sean Pinkney | — | Speaker | Population Effect Estimation in Bayesian Hierarchical Models using Sum-to-Zero Constraints | — |
| Soham Mukherjee | — | Speaker | Latent variable estimation with composite Hilbert space Gaussian processes | — |
| Steve Bronder | — | Workshop | Contributing to Stan: A Developer’s Guide to the Core, Interfaces, and First Contributions | — |
| Steve Bronder | — | Speaker | Embedded Laplace Approximation in Stan | — |
| Teemu Säilynoja | — | Workshop | Bayesian model diagnostics: Workflows and software tools | — |
| Tobias Moskowitz | — | Speaker | Luck, skill, and the battle of the sexes: analyzing tennis | — |
| Ville Laitinen | — | Speaker | An Introduction to Probabilistic Data Analysis with Stan on the Carpentries Platform | — |
| Yiqiu Dong | — | Workshop | Bayesian Inference for Sparsity-Promoting and Edge-Preserving Priors in Probabilistic Programming | — |
| Zeno Romero | — | Speaker | Probabilistic Matrix Completion for Chemical Engineering Applications | — |