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The AI4Europe Reproducibility Initiative

Reproducibility is at the core of solid scientific and technical research. The ability to repeat the research that is produced is a key approach for confirming the validity of a new scientific discovery. Ensuring the robustness and trustworthiness of science that is done using computing and data is critical. The inability to reproduce the results of an experiment can lead to a range of consequences, including the retraction of research at the conference / journal that published it. Furthermore, fostering reproducibility facilitates dissemination, comparison, and adoption of research. Therefore, it can also contribute to increasing the impact and enhancing the visibility of articles.
The European Project AI4Europe aims at building a shared computing and data infrastructure that will provide AI researchers, educators, and students across scientific fields and disciplines with access to compute resources and data, along with appropriate educational tools. Inside the project, the AI4Europe Reproducibility Initiative focuses on promoting reproducibility in the field of artificial intelligence (AI) by establishing specific standards and practices. This tutorial provides an overview of the project’s mission and the significance of reproducibility in AI research. By ensuring that AI findings can be replicated and validated, reproducibility enhances trustworthiness and facilitates advancements in the field. The tutorial also explores existing reproducibility initiatives and introduces the AI4Europe Reproducibility Initiative, which incorporates standardized documentation, a federated computing infrastructure, and dedicated reproducibility tools to support reproducible research in AI.

The AI4Europe Reproducitility Inititative

  • Reproducibility in AI and its importance
  • Existing Reproducibility Initiatives
  • The AI4Europe Project Overview and Mission
  • The AI4Europe Reproducibility Initiative

Prof. Barry O’Sullivan, University College Cork

Professor Barry O’Sullivan, FAAAI, FAAIA, FEurAI, FIAE, FICS, MRIA, is an award-winning academic working in the fields of artificial intelligence, constraint programming, operations research, AI/data ethics, and public policy. He contributes to several global Track II AI diplomacy efforts at the interface of military, defence, intelligence, and AI.

Professor O’Sullivan is a full professor at the School of Computer Science & IT at University College Cork, Ireland, and a member of its Governing Body. He is founding Director of the Insight SFI Research Centre for Data Analytics at UCC and Director of the SFI Centre for Research Training in AI. He is an Adjunct Professor at Monash University.

Professor O’Sullivan has been involved in winning over €300m in R&D funding and he  is the Principal Investig of the Horizon AI4Europe Project. More information on his website

Dr. Gabriel Gonzalez-Castane, University College Cork

Dr. Gabriel González Castañé works as a EU Grant Manager and Senior Research Co-ordinator at the Insight-Centre for data analytics at University College Cork. He holds a PhD in Computer Science and Technology from University Carlos III of Madrid, focusing on applied modeling and simulation of energy-aware Cloud Computing environments. 

Gabriel joined Dublin City University in 2015, where he led the simulation work package in the CACTOS FP7 project. He contributed to proposal development and successfully secured funding for the 4.6 million RECAP H2020 EU project. Afterwards, Gabriel relocated to the University College Cork and became the technical coordinator of the CloudLightning H2020 project. In Insight-Centre for data analytics, Dr. Gabriel González Castañé is currently involved in various industrial projects.

Dr. Gabriel González Castañé is the Technical Coordinator of the AI4Europe Project. More information on his website.

Dr. Rafael Tolosana-Calasanz, University of Zaragoza

Dr. Rafael Tolosana-Calasanz is an Associate Professor at the Computer Science Department of the University of Zaragoza. With a strong commitment to promoting scientific reproducibility, he is involved in the management of different reproducibility initiatives, like the SC’23 Reproducibility Initiative and the ICPP’23 reproducibility initiative. In addition to conference-level initiatives, Dr. Tolosana-Calasanz is at the forefront of the IEEE Transactions on Parallel and Distributed Systems Reproducibility Initiative, as the associate editor-in-chief for reproducibility.

Dr. Tolosana-Calasanz has been recognized as a co-author of the first reproducibility artifact published in the IEEE Transactions on Parallel and Distributed Systems. This artifact serves as a benchmark for researchers and showcases his expertise in conducting reproducible research.

Furthermore, Dr. Tolosana-Calasanz is leading the AI4Europe Reproducibility Initiative. More information on his website.

Tutorial Slides

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