| Aug 08, 2026 | Our paper “SPRIG: Semantic-ID-enhanced Paths for Knowledge Graph-based Generative Recommendation” has been accepted at ACM CIKM 2026 🎉 SPRIG is a generative recommender that integrates Semantic IDs—discrete codes derived from item content such as text and audio—into knowledge-graph path reasoning, grounding recommendations in structured item relationships while achieving competitive performance with fewer parameters and lower compute cost. |
| Sep 22, 2025 | I’m attending ACM RecSys 2025 in Prague (Sept 22–26), where I’ll present our JAM paper (“Just Ask for Music”) and co-organize the DaQuaMRec workshop — come say hi! |
| Jul 03, 2025 | Our paper “Just Ask for Music (JAM): Multimodal and Personalized Natural Language Music Recommendation” has been accepted at ACM RecSys ‘25 🎉 Work done in collaboration with Deezer Research! JAM enables personalized music recommendation from natural language, combining long-term user preferences with short-term intent from text queries across multiple item modalities (audio, lyrics, metadata). |
| May 19, 2025 | I’m happy to share that I’m starting a new position as Machine Learning Engineer at Criteo! I’m joining the Recommendation Models team, where we build scalable and personalized product recommendation engines for user-based and contextual traffic—optimizing performance across diverse business models. |
| Apr 01, 2025 | I’m happy to share that I’m co-organizing the First International Workshop on Data Quality-Aware Multimodal Recommendation (DaQuaMRec), taking place at RecSys 2025 in Prague! |
| Oct 31, 2024 | I defended my thesis “Explainable and Fair Music Recommender Systems”! I am now a PostDoc at the institute :) |
| Sep 12, 2024 | I got the award as best student paper at the European Conference on Machine Learning ECMLPKDD ‘24 taking place in Vilnius, Lithuania. It has been a thrilling experience to share my work in the main room in front of the crowd! |
| Jun 05, 2024 | Super happy that my research paper “Modular Debiasing of Latent User Representations in Prototype-based Recommender Systems” has been accepted at the European Conference on Machine Learning! |
| Mar 08, 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. |