Research Meeting 27014
Advancing Open Machine Learning
( Jan 04 – Jan 08, 2027 )
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Please use the following short url to reference this page:
https://www.dagstuhl.de/27014
Organizers
- Pieter Gijsbers (TU Eindhoven, NL)
- Jan van Rijn (Leiden University, NL)
- Joaquin Vanschoren (TU Eindhoven, NL)
Contact
- Heike Clemens (for administrative matters)
This Dagstuhl research meeting brings together key researchers active in building open source AI research infrastructure to address the fragmented digital infrastructure underlying modern machine learning research. While machine learning has become a cornerstone of scientific discovery, disconnected platforms and lack of standardization limits the interoperability, reproducibility, and reusability of datasets, models, and experiments. By bringing together experts from machine learning, research software engineering, digital research infrastructure, and open science, the seminar will focus on three core challenges: platform interoperability, optimizing end-to-end research workflows, and ensuring the long-term governance and sustainability of open ML ecosystems. Ultimately, the workshop seeks to develop a shared roadmap to foster interdisciplinary collaboration to make machine learning research more FAIR (Findable, Accessible, Interoperable, and Reusable), and build new interoperable infrastructure leveraging modern technologies.
Creative Commons BY 4.0
Joaquin Vanschoren, Pieter Gijsbers, and Jan van Rijn
Classification
- Machine Learning
Keywords
- AI
- machine learning
- research infrastructure
- interoperability
- reproducibility
