About
Thomas Elmar Kolb is a PreDoc Researcher at Technische Universität Wien, affiliated with the Data Science group (E194-04) and the Curriculum Commission for Business Informatics. His research focuses on Recommender Systems, User Modeling, and Generative AI, emphasizing fairness, bias, and cross-domain applications.
Recent research trends in his work include:
- Advancing fairness metrics in news recommendation systems
- Integrating Large Language Models (LLMs) for cross-domain recommendation
- Developing Austrian language polarity resources (ALPIN Dictionary)
- Exploring the interplay between trust and serendipity in user experiences
- Analyzing user roles in online forums for behavioral modeling
Supervisions include diploma theses on group fairness, podcast recommendation systems, and populism detection. Key projects involve the 2022-2028 CDL-RecSys initiative and the 2020-2021 DYSEN project on dynamic sentiment analysis.
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