PymCon 2020
An asynchronous-first virtual conference for the Bayesian community
October 31st
Africa/Asia/Europe: 9-15 UTC
Americas: 9-15 UTC-7

We believe in building a community as much as we believe in building code.

PyMCon 2020 is an asynchronous-first virtual conference for the Bayesian community

We believe that the PyMC project is more than just a codebase. It is also a community that is interested not only in statistical methods and code, but also in sharing knowledge and helping others - whether they be Bayesian veterans or new to the world of open source. The purpose of this conference is to better our community, just as we better our code .

The goals of the conference are to:

  • Create a space and time for community members to meet each other and interact

  • Record and organize the expertise and experience around PyMC

  • Help folks find ways to contribute to PyMC, authentic to themselves

PyMCon is a totally volunteer run conference with help from people like you.

Keynote Speakers

Chris Fonnesbeck

Keynote speaker and PyMC BDFL

Viola Priesemann

Keynote speaker

Aki Vehtari

Keynote speaker

Planning Committee

Ravin Kumar

Executive Chair

Ravin is a proponent of open source, but more importantly open knowledge and the communities that surround them.

Thomas Wiecki

Executive Chair

Advocate for Bayesian methods and probabilistic programming

Oriol Abril-Pla

Diversity Chair

Trying to keep an open yet skeptical mind by contributing to open source software+statistics

Sid Ravinutala

Marketing Chair

International Development. Statistics/data science for international development. Sounds more confident than he is.

Hector Muñoz

Program Chair

Hector is a Bayesian and open source enthusiast who enjoys learning how to build models for complex systems.

Quan Nguyen

Program Chair

Someone with very flat priors

Chris Krapu

Program Committee

PyMC3 Enthusiast, Researcher at Oak Ridge National Laboratory, Tennessee

Cem Tabakci

Volunteer Chair

Opens to any kind of knowledge and believes asking questions helps to solve most of the problems

Colin Carroll

Marketing Committee

Colin is a contributor to PyMC3 and ArviZ. He is enthusiastic about open source science, data visualization, and his small dog Pete.

Alex Andorra

Diversity Chair

ArviZ & PyMC Dev, Modeler @ PyMC | Labs, Host of 'Learning Bayesian Statistics' Podcast 🎙️, Open source & Nutella enthusiast

Maria Gorinova


Probabilistic Programming PhD student at University of Edinburgh

Vianey Leos Barajas


Assistant Professor in Statistical Sciences and the School of the Environment at the University of Toronto.

Abhay Goyal

Committee Member

Msc at Stony Brook University

Christian Luhmann

Technology Committee

Faculty at Stony Brook University focusing on computational (often Bayesian) models behavior-related data.

Corrie Bartelheimer

Planning Committee

Data Scientist enthusiastic about Bayesian stats, hierarchical models and waffles.