Forschungstreffen 27014
Advancing Open Machine Learning
( 04. Jan – 08. Jan, 2027 )
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Organisatoren
- Pieter Gijsbers (TU Eindhoven, NL)
- Jan van Rijn (Leiden University, NL)
- Joaquin Vanschoren (TU Eindhoven, NL)
Kontakt
- Heike Clemens (für administrative Fragen)
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.
Joaquin Vanschoren, Pieter Gijsbers, and Jan van Rijn
Klassifikation
- Machine Learning
Schlagworte
- AI
- machine learning
- research infrastructure
- interoperability
- reproducibility

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