news

Mar 8, 2024 I have been invited to review papers for the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD).
Sep 10, 2023 I’m happy to share that the video of my presentation at RecSys’22 in Seattle is also available on YouTube now. If you are interested in explainable recommendations using prototypes, check it out ;)
Apr 27, 2023 I had a 2 hours presentation at my institute about the basics of Fairness in Machine Learning. Slides are here!
Apr 17, 2023 This year I will be the reviewer for papers at RecSys, ACM Multimedia, workshop on Human-Centric Music Information Research (satellite event of ISMIR), and for a manuscript in ACM Transactions of Recommender Systems (TORS)
Sep 11, 2022 The Ars Electronica Festival is over. We had such a blast at our exhibit Black Holes of Popularity! In case you missed you can check the teaser video here.
Jul 11, 2022 Our research paper “ProtoMF: Prototype-based Matrix Factorization for Effective and Explainable Recommendations” has been accepted at RecSys 2022! Looking forward to travel to Seattle this September.
Apr 14, 2022 The article “Explainability in Music Recommender Systems” will appear in the the Summer 2022 Issue of the Ai Magazine. The article is the result of a very enjoyable and productive collaboration with my supervisor Markus Schedl and Darius Afchar, Romain Hennequin, Elena V. Epure, and Manuel Moussallam from Deezer Research.
Apr 13, 2022 The demo paper “EmoMTB: Emotion-aware Music Tower Blocks” has been accepted to the ACM International Conference on Multimedia Retrieval. I will travel to Newark, NJ, USA to present our demo to the guests of the conference.
Feb 24, 2022 The project proposal “Black Holes of Popularity” for the Linz Ars Electronica Festival 2022 has been accepted and will exhibited at this year’s festival! I will lead the project as PI for seven months together with my colleague Oleg Lesota and my supervisor Markus Schedl.
Jan 25, 2022 The article paper “Explainability in Music Recommender Systems” is now available on arxiv.