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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:
Supercharge your research with the latest scientific software showcased in the Journal of Open Source Software (JOSS). Hear directly from authors on their work, their motivations, and new ways open source software can accelerate your work.
Hosted by editor-in-chief Arfon Smith and founding editor Abby Cabunoc Mayes, each episode features an interview with different authors of published papers in JOSS. Tune in to learn about the latest developments in research software engineering and open science, and how they are changing the way research is conducted.
New episodes every other Thursday.
View all episodes
By The Journal of Open Source Software#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:
Supercharge your research with the latest scientific software showcased in the Journal of Open Source Software (JOSS). Hear directly from authors on their work, their motivations, and new ways open source software can accelerate your work.
Hosted by editor-in-chief Arfon Smith and founding editor Abby Cabunoc Mayes, each episode features an interview with different authors of published papers in JOSS. Tune in to learn about the latest developments in research software engineering and open science, and how they are changing the way research is conducted.
New episodes every other Thursday.