Joseph Wonsil

Joseph Wonsil

he/him

PhD Candidate researching computational reproducibility and data provenance

About me

I am a PhD Candidate in Computer Science in the Systopia Lab at The University of British Columbia and an Adjunct Assistant Professor at Madonna University. My research interests include computational reproducibility, data provenance, human-computer interaction, and combining those three! I am currently exploring how to make scientific reproducibility more accessible for end-users, particularly for scientists who do not necessarily have formal computer science training. With the current availability of powerful AI models, I believe our tools should help us understand and facilitate our work, not just do it for us. We should also be able to investigate the processes that created the models upon which we increasingly rely. Driven by this goal, I’ve worked on reproducibility and provenance for the Tribuo machine-learning framework and data provenance for large-scale data processing during an internship with Oracle.

Previously, I have worked on provenance-based debuggers, nano-satellite computer systems, geospatial public health analyses, and bringing technology to theater.

Education

  • Ph.D in Computer Science, The University of British Columbia, 202X (expected)
  • M.S. in Computer Science, The University of British Columbia, 2021
  • B.A. in Computer Science, Environmental Science, and Geospatial Science, Carthage College, 2019

Recent Publications

  • Joseph Wonsil, Rúbia Guerra, Adam Pocock, Jack Sullivan and Margo Seltzer, "Raising the Reproducibility Bar." In the proceedings of Proceedings of the 2025 ACM Conference on Reproducibility and Replicability, 2025. View Paper

  • Joseph Wonsil, Nichole Boufford, and Margo Seltzer, "Experience with Reproducibility and Consistency in Writing an Academic Paper." In the proceedings of Proceedings of the 2025 ACM Conference on Reproducibility and Replicability, 2025. View Paper

  • Adam Craig Pocock, Joseph Wonsil, Romina Mahinpei, Jack Sullivan, Margo Seltzer, "Provenance Design and Evolution in a Production ML Library." In Championing Open-source DEvelopment in ML Workshop@ ICML25. View Paper