Holger Hoos

Professor of Machine Learning, Leiden University

Holger H. Hoos is Professor of Machine Learning at Universiteit Leiden (the Netherlands) and Adjunct Professor of Computer Science at the University of British Columbia (Canada), where he also holds an appointment as Faculty Associate at the Peter Wall Institute for Advanced Studies. He is a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) and past president of the Canadian Association for Artificial Intelligence / Association pour l'intelligence artificielle au Canada (CAIAC). Holger's research interests span artificial intelligence, empirical algorithmics, bioinformatics and computer music. He is known for his work on machine learning and optimisation methods for the automated design of high-performance algorithms and for his work on stochastic local search. Based on a broad view of machine learning, he has developed - and vigorously pursues - the paradigm of programming by optimisation (PbO); he is also one of the originators of the concept of automated machine learning (AutoML). Holger has a penchant for work at the boundaries between computing science and other disciplines, and much of his work is inspired by real-world applications. In 2018, together with Morten Irgens (Oslo Metropolitan University) and Philipp Slusallek (German Research Center for Artificial Intelligence), Holger launched CLAIRE, an initiative by the European AI community that seeks to strengthen European excellence in AI research and innovation (claire-ai.org). CLAIRE promotes excellence across all of AI, for all of Europe, with a human-centred focus and aims to achieve an impact similar to that of CERN. The initiative has attracted major media coverage in many European countries and garnered broad support by more than 1000 AI experts, more than one hundred fellows of various scientific AI associations, many editors of scientific AI journals, national AI societies, top AI institutes and key stakeholders in industry and other organisations (for details, see claire-ai.org).

Holger is speaking at

Focus Track 3 - Market uptake: Bringing AI and Data Sciences to Practice
November 4, 2020
2:00 pm - 3:30 pm

Speakers

Description

Concept:
During this session, we will explore potential and existing models of collaboration/federation in cross-border initiatives that can be applied in a practical / realistic way to foster data driven innovation at European level, and make this innovation available and accessible to all actors in the European data landscape, in particular SMEs and Start-ups, as it is aimed in the project EUHubs4Data. Starting from a general view on needs, benefits and models of a federation, we will focus on specific and concrete aspects such as governance and structure, a federated catalogue / offer (including data sources, data governance, delivery of joint services and a common training programme), potential legal or organisational barriers, etc. We will also count with the experience of actors involved in existing and different types of federation and networks.
 
Objectives:
 
The expected outcome from this workshop aims to be a set of recommendations about the best options for each of the aspects considered, that could contribute, in the scope of EUHubs4Data project, to the establishment of federated network of data-driven experimentation facilities in Europe (with special focus on AI and Data service innovation development and experimentation), find synergies, share knowledge and assets, and let small and medium size actors on each region to benefit from latest European advances on those fields.

For more information on the EUHubs4Data project visit: https://euhubs4data.eu/ 

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