Thomas Elmar Kolb

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.