Dominik Kowald
Professor Of AI-based Information Retrieval In Digital Humanities
Graz, Styria, Austria
Summary
👤
Senior🎓
Top SchoolDominik Kowald is a professor and research leader specializing in AI-driven information retrieval and recommender systems with 12 years of experience across academia and industry. He leads FAIR-AI research at Know-Center and heads the new professorship for AI-based Information Retrieval in Digital Humanities at the University of Graz, bridging methodological rigor with real-world projects. Holding a PhD with honors and a Habilitation in Applied Computer Science from TU Graz, he combines deep research credentials with hands-on software development roots dating back to .NET industry work. His work emphasizes fairness and reproducibility in AI for cultural and social data, reflecting a rare blend of humanities-aware perspectives and technical expertise. Beyond publications and project leadership, he translates complex research into applied systems through collaborative COMET and EU projects, making him a pragmatic scholar who ships research into practice.
12 years of coding experience
7 years of employment as a software developer
Habilitation, Applied Computer Science, Habilitation, Applied Computer Science at Technische Universität GrazMatura, Business Informatics, Matura, Business Informatics at HTL BULME Graz
German, English
Github Skills (5)
benchmarking10
recommendation-engine10
recommender10
recommender-system10
python-scripts9
Programming languages (2)
Github contributions (5)
domkowald/FairRecSys
Aug 2019 - Feb 2022
Python scripts for studying bias in recommender systems
Contributions:20 commits, 18 pushes, 2 branches in 2 years 6 months
python-scriptsrecommender-systemrecommendersystemsbias
learning-layers/TagRec
Apr 2014 - May 2020
Towards A Standardized Tag Recommender Benchmarking Framework
Contributions:8 releases, 165 commits, 88 pushes in 6 years 2 months
benchmarkingrecommenderrecommender-systemrecommendation-enginetaggingtools
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