Holger H. Hoos is an Alexander von Humboldt Professor of AI at RWTH Aachen University (Germany),
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 Computing Machinery (ACM),
Fellow of the Association for the Advancement of Artificial Intelligence (AAAI),
Fellow of the European Association for Artificial Intelligence (EurAI),
chairman of the board of the Confederation of Laboratories of Artificial Intelligence Research in Europe (CLAIRE),
vice-president of EurAI, past president of the Canadian Association for Artificial Intelligence (CAIAC),
member of the Advisory Board and former Editor-in-Chief of the Journal of Artificial Intelligence Research (JAIR)
and leader of the VISION coordination mandate for the four European networks of centres of excellence in AI established in 2020.
Holger's research is aimed at methodological and technological advances in human-centred AI, AI for Good and AI for All.
Specifically, he seeks to improve the efficiency of AI methods, by
automatically increasing performance and reducing resource needs;
and to broaden access to and use of cutting-edge AI methods.
Overall, Holger and his group develop and study AI methods that augment rather than replace human intelligence,
and that help human experts to overcome their biases and limitations.
Known for his work on machine learning and optimisation methods for the automated design of high-performance algorithms
and on stochastic local search, Holger 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;
much of his work is inspired by and has broad impact on real-world applications.
In 2018, together with Morten Irgens (OsloMet) and Philipp Slusallek (DFKI),
Holger launched CLAIRE, an initiative by the European AI community that seeks to strengthen European excellence in AI research
and innovation. Incorporated as a non-profit international organisation in 2019,
CLAIRE promotes excellence across all of AI, for all of Europe, with a human-centred focus
(for details, see claire-ai.org).
In 2021, CLAIRE received, jointly with the European Laboratory for Intelligent Systems (ELLIS),
the German AI Innovation Prize (Deutscher KI-Innovations-Preis), in recognition of outstanding contributions
to development and research in artificial intelligence; valued at 100 000 Euros, this prize is the largest of its kind
In November 2021, Holger has been selected for an Alexander von Humboldt Professorship in AI,
Germany's most highly-endowed research award, which honours its recipients for their outstanding
research record and aims to facilitate long-term and groundbreaking research contributions.
Supported by this award and substantial additional resources made available by the university,
he started building a new research group at RWTH Aachen University (Germany), dedicated
to methodological and technological advances in human-centred AI, AI for Good and AI for All,
in January 2022. He also serves on the board of directors of the RWTH AI Center.
- Alexander von Humboldt Professor of Artificial Intelligence, RTWH Aachen University, Germany
- Professor of Machine Learning, Universiteit Leiden, The Netherlands
- Adjunct Professor of Computer Science, The University of British Columbia, Canada
- Chair of the Board, Confederation of Laboratories for AI Research in Europe (CLAIRE)
Holger H. Hoos
Chair for AI Methodology (AIM)
RWTH Aachen University
Office: Room 316
Phone: +49 241 802 1451 (office), +49 241 802 1452 (secretariat)
Holger H. Hoos
Leiden Institute of Advanced Computer Science (LIACS)
Niels Bohrweg 1
2333 CA Leiden
Office: Snellius Gebouw, Room 124
Phone: +31 71 527 5777 (office), +31 71 527 7096 (secretariat)
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