Planning a MSCA-PF proposal: Turning Music Discoverability into an Auditable Problem
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/