StanCon 2024

StanCon 2024

Dates: September 9 - 13th 2024

Stan is a widely used Bayesian inference software, which has found many applications across academia and industry, including political science, pharmacometrics, epidemiology, astrophysics, advertising, and more. The conference brings together both veteran and novice users, and serves as a focused event to discuss practical deployment and application of Bayesian modeling.

The main conference is Tuesday 10th - Thursday 12th.

Monday 9th afternoon we will have a half-day of workshops, including an introductory tutorial on Stan, and we will have an additional day of workshops on Friday 13th.

The conference comprises one and half day of tutorial (with introductory and advanced courses) and three days of contributed talks.

For any questions, please reach out to stancon2024 at mc-stan dot org.


Sponsors support StanCon in various ways and help us book venues, create high quality online content, provide scholarships for early career researchers and participants from underrepresented groups in the sciences, and more.

If you’re interested in sponsoring StanCon, please email

We thank our current sponsors and supporting institutions: Daiichi-Sankyo, Metrum Research Group, Jumping Rivers, Taylor and Francis, NumFocus, the Oxford Internet Institute, and the Max Planck Institute for Evolutionary Anthropology.

Keynote speakers

These are the confirmed keynote speakers:

  • Chris Wymant (Senior Researcher, Pandemic Sciences Institute, Oxford University)
    Bayesian multilevel causal modelling of the frequency and implications of having two HIV infections

  • Vianey Leos Barajas (Assistant Professor, Department of Statistical Sciences & School of the Environment, University of Toronto)
    From the Depths to the Stars: How Modeling Shark Movements Illuminates Star Behavior

  • Sebastian Weber (Director Statistical Methods & Consulting, Advanced Exploratory Analytics, Novartis Pharma AG, Basel)
    Applied modeling for drug development

  • Mitzi Morris (Stan Developer, Columbia University)
    The Pragmatic Probabilistic Programmer

Talk titles and abstracts will be posted soon!

Call for proposals

We’re now accepting proposals for contributed talks and tutorials. Proposals are reviewed by the organization committee on a rolling basis.

Contributed talks are 15 minutes long, with an additional 5 minutes for questions. Talks can cover a diversity of topics, including:

  • Data analysis and modeling using Stan in any field
  • Software development within Stan or the Stan ecosystem, and more broadly software relevant to Stan users
  • Methodological development for Bayesian modeling

To submit a proposal for a talk, please fill out this form.

Tutorials are either half-a-day or one day long, with each half-day 2 or 3 hours long. Tutorials should be introductory, though certain pre-requisites may be assumed (e.g. basic knowledge of Stan, R, Python, probability, etc.). When submitting a proposal be specific about the pre-requisites.

We will provide an “introduction to Stan” tutorial, aimed at participants who have not used Stan before.

To submit a proposal for a tutorial, please fill out this form.


Below are the confirmed talks (in no particular order). These are talks which have been accepted by the scientific committee and for which speakers have confirmed their attendance.

  • Ethan Budge (Brigham Young University)
    Sharing the Spotlight: How Artist Collaboration affects Song Popularity

  • Brynjólfur Gauti Guðrúnar Jónsson
    Copulas in Stan: Modeling Spatial Dependence in Generalized Extreme Value Distributions

  • Xingyao (Doria) Xiao (UC Berkeley)
    Bayesian Identification, Estimation, and Diagnostic Techniques for Growth Mixture Models using Stan

  • Bob Carpenter (Flatiron Institute)
    What’s your favorite sushi? Combining ranking and rating models in Stan

  • Chirag Modi (Flatiron Institute)
    Atlas: Adapting Trajectory Length and Stepsize

  • Jari Turkia (University of Eastern Finland)
    Inferring Personalized Diet Recommendations Using a Conditional Mixture of Health Outcomes and Personal Preferences

  • Simon Maskell (Liverpool University)
    Running Multiple Short MCMC Chains on a GPU Using JAX for Fast Inference with Stan

  • Brian Ward (Flatiron Institute)
    Stan without installing Stan? How (and why) to sample inside your browser

  • Conor Goold (Ledger Investing)
    Joint estimation of body and tail loss development factors in insurance: a case study using hidden Markov models in Stan

  • David Kohns (Aalto University)
    The ARR2 prior: flexible predictive prior definition for Bayesian auto-regressions

  • Laura Jenniches (Helmholtz Institute for RNA-based Infection Research)
    Advancing functional genomics analysis with Stan: Case studies in RNA decay and pathogen invasion models

  • Aditya Ravuri (Cambridge University)
    GPLVM Equivalences in UMAP, Isomap and Beyond

  • Nicolas Irons (University of Washington) Evaluating and optimizing non-pharmaceutical interventions to combat infectious disease transmission 
    Causally sound priors for binary experiments

  • Adam Gorm Hoffmann (University of Copenhagen)
    Efficient Hierarchical Gaussian Process Regression

  • Jonas Mikhaeil (Columbia University)
    Hierarchical Bayesian Models to Mitigate Systematic Disparities in Prediction with Proxy Outcomes

  • Jouni Helske (University of Turku)
    dynamite: An R Package for Dynamic Multivariate Panel Models

  • Yann McLatchie (Univeristy College London)
    Predictive performance of power posteriors

  • Judith Bouman (University of Bern)
    Bayesian workflow for time-varying transmission in stratified compartmental infectious disease transmission models

  • Sean Pinkney (Stan Developer)
    Structured Correlation Matrices


Confirmed tutorials will be posted here as they get accepted. The schedule for tutorials is tentative and subject to change.

Monday 9th

  • Richard McElreath (Max Planck Institute for Evolutionary Anthropology)
    Introduction to Stan

  • Sean Pinkney (Stan Developer) Bayesian hierarchical models in Stan

Friday 13th

  • Anna Elisabeth Riha (Aalto University), Adam Howes (CDC), Seth Flaxman (Imperial College London), Elizaveta Semenova (Imperial College London) Bayesian optimisation with Stan

  • Will Pearse (Imperial College London)
    Biodiversity modelling and forecasting


Tickets can be purchased at link.

Prices for early bird registration are listed below:

  • Students (Conference only) £199.0
  • Students (Conference and tutorials) £299.0
  • Academics (Conference only) £299.0
  • Academics (Conference and tutorials) £449.0
  • Industry (Conference only) £599.0
  • Industry (Conference and tutorials) £799.0

The early bird registration has been extended from July 1st to July 15th!
After July 15th, all ticket prices for non-student participants increase by £100.0 (prices for students will not increase).


The purpose of the StanCon scholarship is to make StanCon a more accessible and inclusive event.

Participants who require financial assistance to attend the conference should fill out an application form.

The StanCon scholarship covers registration for the tutorial and the main conference, as well as local lodging. Scholarships are awarded on a need-base, and prioritize early career scientists, including students and post-docs, and members of underrepresented groups in STEM.

Applications are accepted and reviewed on a rolling basis, and scholarships are awarded based on available funds.


The conference will be held at the Department of Engineering Science, University of Oxford, Thom Building, Parks Road, Oxford OX1 3PJ.

There are several options for securing your accommodation nearby. These include B&Bs, colleges, or hotels. Please see some examples below at various price points.

We also recommend looking into any available rooms at Oxford Colleges or SpeedyBooker, many of which offer ensuite accommodation with breakfast in an Oxford Hall and are an idyllic way to experience Oxford. Please note not all college accommodation is located in central Oxford, not all rooms offer hotel style amenities, and many have shared bathrooms, so please ensure you look for these when booking.


If you are travelling from within the UK, taking a bus or train directly into Oxford would be the easiest option. Check the national providers for appropriate routes.

If you are travelling from outside the UK, we would suggest first to travel into London via train or plane. If you are travelling via plane, and arriving/departing via Gatwick or Heathrow airport, we recommend booking a return ticket on the airline – a bus service that will take you directly from the airport to the central Oxford bus station at Glouster Green. If you are arriving into London via train, and arriving/departing from St Pancras Station, we recommend taking the underground tube to Paddington Station and then a train to Oxford Station. Tickets can be bought at Great Western Railway, Trainline, and many other online providers. You can also purchase train tickets at the station if preferred. Travelling via the London underground is easiest using a contactless card. Alternatively, there are regular buses from London and Oxford through the “Oxford Tube” that provide travel at an affordable price.

For further information, please see the university’s advice on How to get to Oxford and some advice for international travel into Oxford, however, please check any travel independently as some information may be outdated.


  • Michael Collyer (University of Oxford)
  • Joss Wright (University of Oxford)
  • Richard McElreath (Max Planck Institute for Evolutionary Anthropology)
  • Elizaveta Semenova (Imperial College London)
  • Ben Lambert (University of Oxford)
  • Seth Flaxman (University of Oxford)
  • Charles Margossian (Flatiron Institute)
  • Juliette Unwin (University of Bristol)
  • Will Pearse (Imperial College London)
  • Makkunda Sharma (University of Oxford)