Tackling the Machine Learning Reproducibility Crisis – KJ Schmidt & Aristana Scourtas on Foundry-ML

#19: KJ Schmidt & Aristana Scourtas join Arfon and Abby to discuss Foundry-ML, a platform designed to simplify using machine learning datasets, highlighting its development, impacts, and their career advancements post-project.

KJ just started a position at the Institute for Genomic Medicine within Nationwide Children's Hospital. Aristana is a Product and Research Manager at The Library Innovation Lab at Harvard Law School. KJ and Aristana both worked on Foundry-ML during their time working at UChicago and Globus.

You can follow Aristana on LinkedIn https://www.linkedin.com/in/aristana/ and Twitter/X @aristana_s. You can follow KJ on Twitter/X @kj_schmidt or LinkedIn https://www.linkedin.com/in/schmidtkj/.

Episode highlights:

[01:54] Beginning of Interview with KJ Schmidt and Aristana Scourtas [02:02] What is Foundry-ML? [04:02] The Role of Globus in Foundry-ML [05:29] Reproducibility in Machine Learning [06:45] Applications and Collaborations [09:15] New Roles and Future Plans [11:01] Maintaining Foundry-ML [12:37] Sustainability in Open Source [13:12] Community Building in Open Source [21:49] Challenges and Lessons Learned [24:28] Publishing in JOSS [25:38] Closing Remarks and Contact Information

Links:

• JOSS paper: https://joss.theoj.org/papers/10.21105/joss.05467
• Foundry repository: https://github.com/MLMI2-CSSI/foundry
• Website: https://foundry-ml.org/
• Movement Building from Home
• KJ on Twitter/X @kj_schmidt or LinkedIn https://www.linkedin.com/in/schmidtkj/
• Aristana on LinkedIn https://www.linkedin.com/in/aristana/ and Twitter/X @aristana_s
• The Journal of Open Source Software (Twitter/X, blog)
• @arfon on (fosstodon, Linkedin, GitHub, website)
• @abbycabs on (Twitter/X, hachyderm, bsky, Linkedin, GitHub, website)
• Donate to JOSS

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