Alessandro B. Melchiorre

Alessandro B. Melchiorre

Hola!

I am a Ph.D. student at the Institute of Computational Perception and at the Multimedia Mining and Search Group at the Johannes Kepler University Linz, Austria.

I studied Engineering in Computer Science in my Bachelor at Università degli Studi di Napoli Federico II and in my Master at Sapienza - Università di Roma where I both graduated with full marks.

My main interests revolve around the topics of recommender system algorithms, explainability in AI, and bias & fairness. I am particularly enthusiastic about developing interpretable models and explainability methods for recommender systems, especially in the music domain. I am also interested in investigating the relationships between users’ characteristics and music preference and consumption.


Publications

Peer-Reviewed Journal and Conference Papers

ModDebias screenshot

Alessandro B. Melchiorre, Shahed Masoudian, Deepak Kumar, Markus Schedl
Modular Debiasing of Latent User Representations in Prototype-based Recommender Systems
Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2024), 2024
 Best Student Paper Award

CaliPopExploring screenshot

Oleg Lesota, Stefan Brandl, Matthias Wenzel, Alessandro B. Melchiorre, Elisabeth Lex, Navid Rekab-saz, Markus Schedl
Exploring Cross-group Discrepancies in Calibrated Popularity for Accuracy/Fairness Trade-off Optimization
Proceedings of the 2nd Workshop on Multi-Objective Recommender Systems co-located with 16th ACM Conference on Recommender Systems (RecSys 2022), Seattle, WA, USA, 18th-23rd September, 2022

EMOMTB screenshot

Alessandro B. Melchiorre, David Penz, Christian Ganhör, Oleg Lesota, Vasco Bezold Rosner Fragoso, Florian Friztl, Emilia Parada-Cabaleiro, Franz Schubert, Markus Schedl
EmoMTB: Emotion-aware Music Tower Blocks
Proceedings of the 2022 ACM International Conference on Multimedia Retrieval (ICMR), 2022

ExpMusic screenshot

Darius Afchar, Alessandro B. Melchiorre, Markus Schedl, Romain Hennequin, Elena V. Epure, Manuel Moussallam
Explainability in music recommender systems
AI Magazine, 2022

PopBiasGender screenshot

Oleg Lesota, Alessandro B. Melchiorre, Navid Rekab-saz, Stefan Brandl, Dominik Kowald, Elisabeth Lex, Markus Schedl
Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected?
Proceedings of the 15th ACM Conference on Recommender Systems (RecSys), 2021

LEMONS screenshot

Alessandro B. Melchiorre, Verena Haunschmid, Markus Schedl, Gerhard Widmer
LEMONS: Listenable Explanations for Music recOmmeNder Systems
Proceedings of the 43rd European Conference on Information Retrieval (ECIR), 2021

PersonalityCorrelates screenshot

Alessandro B. Melchiorre, Markus Schedl
Personality Correlates of Music Audio Preferences for Modelling Music Listeners
Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization (UMAP), 2020

PersonalityBias screenshot

Alessandro B. Melchiorre, Eva Zangerle, Markus Schedl
Personality Bias of Music Recommendation Algorithms
Proceedings of the 14th ACM Conference on Recommender Systems (RecSys), 2020