I'm an associate research scholar at Princeton. I mainly teach graph neural networks to do charged particle tracking (https://github.com/gnn-tracking/). I want to discuss how to structure/build ML frameworks for collaborative R&D (providing structure and convenience without constraining creativity). See https://github.com/HSF/PyHEP.dev-workshops/issues/26

Software training for HEP: How can we train physicists to write good software and be prepared for the HL-LHC? I am interested in cross experiment topics an have been working to build up a training center with HSF (https://hepsoftwarefoundation.org/training/curriculum.html). How can we grow this? Interested in this issue: https://github.com/HSF/PyHEP.dev-workshops/issues/7