Vito Bellini

Senior Applied Scientist

I am a Senior Applied Scientist at Amazon Music focused on machine learning, large-scale experimentation, causal inference, and personalization systems that create measurable product impact.

Experience

  1. 2025 - Present Berlin, Germany

    Senior Applied Scientist III, Amazon Music

  2. 2022 - 2025 Amazon Music

    Applied Scientist II

  3. 2020 - 2021 Amazon Music

    Applied Scientist I

  4. 2019 Amazon Music

    Applied Scientist Intern

  5. 2016 - 2017 Polytechnic University of Bari

    Teaching Assistant, Algorithms and Data Structures in Java

Education

  1. 2016 - 2019 PhD

    Computer Science & Engineering, Polytechnic University of Bari

    Research focus on deep learning for recommender systems, interpretability, and explainable recommendation models.

  2. 2013 - 2016 MSc

    Computer Science, Polytechnic University of Bari

    Graduated with work centered on recommender systems in the movie domain.

  3. 2009 - 2013 BSc

    Computer Science, Polytechnic University of Bari

Selected research and workshop papers

A shortlist of conference and workshop publications. For the complete list, use the Google Scholar profile above.

2025

A Unified Recommendation Model for Features Summarization

Vito Bellini, Zhan Shi, Huseyin Yurtseven, Fabian Moerchen, and Emanuele Coviello

3rd Music Recommender Systems Workshop (MuRS 2025), co-located with RecSys 2025

2022

Modeling position bias ranking for streaming media services

Matteo Ruffini, Vito Bellini, Alexander Buchholz, Giuseppe Di Benedetto, and Yannik Stein

The Web Conference 2022

2022

Fair effect attribution in parallel online experiments

Alexander Buchholz, Vito Bellini, Giuseppe Di Benedetto, Yannik Stein, Matteo Ruffini, and Fabian Moerchen

The Web Conference 2022

2020

Guapp: A conversational agent for job recommendation for the Italian public administration

Vito Bellini, Giovanni Maria Biancofiore, Tommaso Di Noia, Eugenio Di Sciascio, Fedelucio Narducci, and Claudio Pomo

IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS)

2018

Knowledge-aware autoencoders for explainable recommender systems

Vito Bellini, Angelo Schiavone, Tommaso Di Noia, Azzurra Ragone, and Eugenio Di Sciascio

Deep Learning for Recommender Systems Workshop (RecSys)

2018

Reflective internet of things middleware-enabled a predictive real-time waste monitoring system

Vito Bellini, Tommaso Di Noia, Marina Mongiello, Francesco Nocera, Angelo Parchitelli, and Eugenio Di Sciascio

International Conference on Web Engineering (ICWE)

2017

Auto-encoding user ratings via knowledge graphs in recommendation scenarios

Vito Bellini, Vito W. Anelli, Tommaso Di Noia, and Eugenio Di Sciascio

Deep Learning for Recommender Systems Workshop (RecSys)

2017

An analysis on time-and session-aware diversification in recommender systems

Vito Walter Anelli, Vito Bellini, Tommaso Di Noia, Wanda La Bruna, Paolo Tomeo, and Eugenio Di Sciascio

Conference on User Modeling, Adaptation and Personalization (UMAP)

2017

Querying deep web data sources as linked data

Vito W. Anelli, Vito Bellini, Andrea Cali, Giuseppe De Santis, Tommaso Di Noia, and Eugenio Di Sciascio

International Conference on Web Intelligence, Mining and Semantics

Patents