Alessandro B. Melchiorre

alessandro.b.mel ((at)) gmail.com

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

My 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, Austria.

I hold both a Bachelor’s and a Master’s degree in Engineering in Computer Science.

news

Jun 05, 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!

selected publications

  1. melchiorre2024modular_preview.png
    Modular Debiasing of Latent User Representations in Prototype-based Recommender Systems
    Alessandro B. Melchiorre, Shahed Masoudian, Deepak Kumar, and 1 more author
    In Proceedings of 2024 Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD) , 2024
  2. melchiorre2022protomf_preview.png
    ProtoMF: Prototype-based Matrix Factorization for Effective and Explainable Recommendations
    Alessandro B. Melchiorre, Navid Rekabsaz, Christian Ganhör, and 1 more author
    In Proceedings of the 16th ACM Conference on Recommender Systems (RecSys) , Seattle, WA, USA, 2022
  3. Article with Deezer
    afchar2022explainability_preview.png
    Explainability in Music Recommender Systems
    Darius* Afchar, Alessandro B.* Melchiorre, Markus Schedl, and 3 more authors
    AI Magazine, 2022
  4. Journal
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    Investigating Gender Fairness of Recommendation Algorithms in the Music Domain
    Alessandro B. Melchiorre, Navid Rekabsaz, Emilia Parada-Cabaleiro, and 3 more authors
    Information Processing & Management (IPM), 2021