Dr. Dominik Kowald is research area manager of the Social Computing team
at the Know-Center, Austria's leading research center for data-driven business and big data analytics.
He has a PhD. (with hons), MSc. (with hons) and BSc. in Computer Science from Graz University of Technology.
He has finished his PhD in October 2017 in the course of the European-funded research project Learning Layers
on cognitive-inspired recommender systems for social tagging and microblogging environments. Currently he is working as key researcher in the DDAI COMET module, and as task lead in the H2020 AI4EU and TRUSTS projects.
His research interests are in the fields of recommender systems, privaccy, fairness and biases in algorithms, Web science and computational social science, in which he has published more than 60 papers so far.
Full cv: ()
Dissertation summary: ( .pdf) ( .pdf)
- Kowald, D., Muellner, P., Zangerle, E., Bauer, C., Schedl, M. & Lex, E. (2021). Support the Underground: Characteristics of Beyond-Mainstream Music Listeners. EPJ Data Science. () ( .pdf) ( link) news
- Muellner, P., Kowald, D., & Lex, E. (2021). Robustness of Meta Matrix Factorization Against Strict Privacy Constraints. In Proceedings of the 43rd European Conference on Information Retrieval (ECIR'2021). Springer. () .pdf
- Kowald, D., Schedl, M., & Lex, E. (2020). The Unfairness of Popularity Bias in Music Recommendation: A Reproducibility Study. In Proceedings of the 42nd European Conference on Information Retrieval (ECIR'2020). Springer. () .pdf
- Lacic, E., Reiter-Haas, M., Kowald, D., Dareddy, M., Cho, J., & Lex, E. (2020). Using Autoencoders for Session-based Job Recommendations. User Modeling and User-Adapted Interaction (UMUAI). Springer. () .pdf
- Kowald, D., Pujari, S., & Lex, E. (2017). Temporal Effects on Hashtag Reuse in Twitter: A Cognitive-Inspired Hashtag Recommendation Approach. In Proceedings of the 26th International World Wide Web Conference (WWW'2017). ACM. () .pdf