PROBPROG 2023 Fall Seminar Series

The International Conference on Probabilistic Programming (PROBPROG) is pleased to announce the start of a new Seminar Series in Probabilistic Programming, to be held monthly in Fall 2023.

Probabilistic programming is an emergent field based on the idea that rich probabilistic models can be efficiently represented as programs in specialized programming languages. This idea has enabled researchers to formalize, automate, and scale up many aspects of modeling and inference; to make modeling and inference accessible to a broader audience of developers and domain experts; and to develop new programmable AI systems that integrate diverse modeling and inference approaches.

The Seminar series will serve as a platform for bringing together researchers and practitioners in probabilistic programming, statistics, ML/AI, and adjacent areas, to advance all aspects of probabilistic modeling, inference, and languages. Invited speakers will have the opportunity to update the broader community about their latest work. The seminar will additionally provide a venue for participants in academia and industry to exchange ideas, experiences, problem domains, and cutting-edge software projects through a breakout room format with open discussion.


The Fall 2023 schedule is as follows (held online via GatherTown):

  • Thu Sep 28, 2023. 11:00 am - 12:30 pm US ET
  • Thu Oct 26, 2023. 11:00 am - 12:30 pm US ET
  • Thu Nov 30, 2023. 11:00 am - 12:30 pm US ET
  • Thu Dec 21, 2023. 11:00 am - 12:30 pm US ET

Submission Tracks

We are soliciting submissions for talks in three tracks.

  1. Probabilistic Programming Research Talks. Talks in this track present novel research that has already been accepted at a peer-reviewed venue (e.g., PLDI, NeurIPS, POPL, AISTATS, OOPSLA, ICML etc.) within the last 18 months. Authors should submit the abstract and full paper of the accepted paper as PDF, specifying the original venue and date of the paper’s acceptance. Slides from previous iterations of the talk may be optionally submitted as well.

  2. Probabilistic Programming in Practice Talks. Talks in this track are focused on demos for systems, languages, and applications of probabilistic programming in practice. Authors should submit a summary describing the main capabilities and/or applications of the system being presented. Preference will be given to submissions that are associated with high-quality open-source demos (e.g. Github repository, online tutorials, IPython notebooks, etc.) that can be presented in the seminar. Examples of supporting materials are given on the submission form.

  3. Discussion Topic Proposal. This track invites proposals for a discussion topic in a community breakout room. Proposed topics may be associated with preliminary work (e.g., workshop papers, arXiv preprint) to help ground the discussion. Submissions are strongly encouraged to include more than one person per topic, including a designated moderator. Preferences will be given to submissions that include a clear problem statement and supporting discussion materials.


Please complete the form on the submissions page. Submissions will be accepted on a rolling basis.


  • Feras Saad (Carnegie Mellon University)
  • Steven Holtzen (Northeastern University)

For any questions, please contact the organizers at