Experience and Outcomes Organizing a Hackathon in the Physical Sciences

Volume 17, Issue 1 (March 2026), pp. 59–64

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@article{jocse-17-1-9,
  author={Aaron Jezghani and Jason Fry},
  title={Experience and Outcomes Organizing a Hackathon in the Physical Sciences},
  journal={The Journal of Computational Science Education},
  year=2026,
  month=mar,
  volume=17,
  issue=1,
  pages={59--64},
  doi={https://doi.org/10.22369/issn.2153-4136/17/1/9}
}

Despite its growing importance in physical sciences, research computing with cluster resources remains difficult to access and sustain, especially in long-term, multi-institutional projects. Challenges include site-specific workflows, evolving software stacks, and rapid changes in hardware post-Generative AI. The Nab collaboration, conducting a precision test of the Standard Model at Oak Ridge National Laboratory, hosted a hackathon to address these issues. Over four half-days, 25 participants engaged in training and collaborative problem-solving across four priority areas, supported by mentors and structured sessions. Post-event surveys showed improved computational knowledge and strong interest in recurring events. This paper shares insights from organizing the hackathon and discusses scalable strategies for computational training in experimental research.