Alessandro B. Melchiorre

Alessandro B. Melchiorre

I am a PostDoc in Machine Learning and Computer Science at the Institute of Computational Perception at Johannes Kepler University Linz, Austria.

My current research is on Generative Retrieval applied to Recommendation and Multimodal Recommender Systems.

My past research specializes in recommender system algorithms, explainable AI, and fairness in machine learning. My work has been published in esteemed conferences and journals such as RecSys, ECML-PKDD, ECIR, AI Magazine, and Information Processing & Management.

Additionally, I led two science communication projects showcased at the international Ars Electronica Festival in Linz,


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