CV
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Table of contents
- General Information
- Education
- Experience
- Selected Publications
- Research Interests
- Skills
- Other Interests
General Information
| Full Name | Marta Moscati |
| Languages | Italian (native), English (C2), German (C1), French (B2), Chinese Mandarin (A1) |
Education
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2021 - present PhD in Computer Science
Johannes Kepler University Linz, Austria - Research on multimodal learning and recommender systems
- Supervising students
- Contributing to the scientific community as chair (publicity, proceedings), program committee, and reviewer
-
2019 PhD in Theoretical Particle Physics
Karlsruhe Institute of Technology (KIT), Germany - Thesis "Lepton Flavour Non-Universality - From Effective Field Theory to Extended Gauge Models"
- Research on new physics models and lepton flavor universality violation
Experience
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2025 - present Applied Scientist (L5)
Albatross AI - Developing effective recommender systems for Albatross AI's customers
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June 2024 - December 2024 Research Intern
Deezer Research Team, Paris, France - User modelling from large-scale music streaming data
- Analysis of user behavior patterns in music consumption
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2021 - present PhD Researcher
Johannes Kepler University Linz, Austria - Multimodal representation learning for recommender systems
- Cold-start recommendation scenarios
- Music information retrieval and emotion-based music recommendation
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2019 - 2021 Postdoctoral Researcher
Karlsruhe Institute of Technology (KIT), Germany - Research in theoretical particle physics
- Focus on lepton flavor universality and beyond Standard Model physics
Selected Publications
-
2026 Face-Voice Association with Inductive Bias for Maximum Class Separation
- M. Moscati, O. Kats, M. Noman, M.Z. Zaheer, Y. Hou, M. Schedl, S. Nawaz. IEEE ICASSP 2026.
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2025 Parameter-Efficient Single Collaborative Branch for Recommendation
- M. Moscati, S. Nawaz, M. Schedl. ACM RecSys 2025.
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2024 A Multimodal Single-Branch Embedding Network for Recommendation in Cold-Start and Missing Modality Scenarios
- C. Ganhör*, M. Moscati*, A. Hausberger, S. Nawaz, M. Schedl. ACM RecSys 2024. (*Equal contributions)
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2023 Integrating the ACT-R Framework with Collaborative Filtering for Explainable Sequential Music Recommendation
- M. Moscati, C. Wallmann, M. Reiter-Haas, D. Kowald, E. Lex, M. Schedl. ACM RecSys 2023.
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2022 Music4All-Onion -- A Large-Scale Multi-Faceted Content-Centric Music Recommendation Dataset
- M. Moscati, E. Parada-Cabaleiro, Y. Deldjoo, E. Zangerle, M. Schedl. ACM CIKM 2022.
Research Interests
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Multimodal Learning
- Cross-modal representation learning
- Audio-visual learning (face-voice association)
- Handling missing modalities in multimodal systems
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Recommender Systems
- Cold-start recommendation
- Music recommendation
- Sequential recommendation
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Music Information Retrieval
- Music emotion recognition
- Multi-modal music retrieval (audio, lyrics, video)
- Music discovery patterns and user behavior
Skills
| Programming Languages | ||||
| Machine Learning | ||||||
| Research | |||||
Other Interests
- Passions: Music, Books, Mathematics, Science
- Activities: Sports, Language learning