Turning Music Discoverability into an Auditable Problem: A Research Journey
The Doctoral Programme in Information Engineering and Computer Science (IECS) organizes the sixth edition of the PI Stories, a series of seminars aimed at providing the opportunity for PhD students to learn the success stories of some of the most talented researchers in the world.
Each speaker will present a research project he/she led as a principal investigator. The presentation will cover the scientific scope of the project and the most important results that the project has achieved. The speakers will also share their own experiences of turning a research idea into a successful project winning a competitive grant.
The events will take place in presence or online on Zoom and will be held in English.
Abstract
Music recommender systems play a central role in shaping how listeners discover artists and how cultural value is distributed online. Despite their societal and economic relevance, these systems remain largely opaque, raising questions about discoverability, representation, and accountability.
In this talk, I will present my MSCA-funded research project focused on auditing music recommender systems from a user-centered perspective. I will discuss the scientific motivations behind the project, the methodological challenges of studying proprietary platforms, and the main results obtained through mixed methods research. Beyond the scientific contributions, the talk will also reflect on the process of transforming an initial research idea into a funded project. I will share practical insights into defining a compelling research question, positioning it within interdisciplinary contexts, and navigating competitive grant applications. The seminar aims to provide participants with both a concrete research case study and a behind-the-scenes perspective on leading a project as a principal investigator. More info: https://aa4md-project.eu/
Bio
Lorenzo Porcaro is a research scientist specializing in recommender systems, with a particular focus on algorithmic auditing. He is currently a Marie Skłodowska-Curie Postdoctoral Fellow at Sapienza University of Rome, leading the project Algorithmic Auditing for Music Discoverability (AA4MD). Lorenzo holds a PhD from Universitat Pompeu Fabra, where his doctoral research explored how diversity in music recommendations shapes listener behavior and perception. Before his PhD, he gained industry experience in music data engineering at SoundCloud and BMAT, and later served as Scientific Project Officer at the European Commission’s Joint Research Centre, contributing to the European Centre for Algorithmic Transparency (ECAT). More info: https://lorenzoporcaro.me/