Music Technology, Machine Learning, Responsible Music AI
I am a Postdoctoral Research Associate in Computer Science at the University of Manchester, and incoming Lecturer at the University of Liverpool. Currently, I work on S+T+ARTS MUSAE, and on the EU H2020 Polifonia project, where I lead the INTERLINK pilot.
My research lies at the intersection of Machine Learning and Music Technology.
I design methods for computational music analysis and information retrieval:
from the detection of structures, emotions, and similarities in music, to
the design of systems for personalised music discovery and recommendation.
Using a computational lens, I seek to investigate the link between
music, memory, and emotions, to derive
knowledge that can be used to improve our
understanding of music, personalise music listening for wellbeing,
support computational creativity and increase engagement in music education.
My research spans across 3 areas: (1) Computational Creativity, (2) Music Personalisation, and (3) Semantic Music Web. All these directions share Music Information Retrieval as the core foundational level, providing computational methods to extract, search and relate knowledge from music. More information is given below.
For a more comprehensive list of publications, check out my Scholar page.
J. de Berardinis, A. Meroño-Peñuela, A. Poltronieri, V. Presutti, in Scientific Data, vol. 10, 641, 2023.
Article | Code | Data | SlidesJ. de Berardinis, A. Meroño-Peñuela, A. Poltronieri, V. Presutti, in Proceedings of the ACM Web Conference 2023, pp. 3873-3882.
Article | Code | SlidesJ. de Berardinis, E. Coutinho, A. Cangelosi, in IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP), vol. 30, 2022.
Article | Code | SlidesJ. de Berardinis, M. Vamvakaris, E. Coutinho, A. Cangelosi, in Transactions of the International Society for Music Information Retrieval (TISMIR), 3(1), 2020.
Article | Code | SlidesE. Coutinho, A. Alshukri, J. de Berardinis, C. Dowrick, in Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers (UbiComp), 2021.
Article | WebpageJ. de Berardinis, E. Coutinho, A. Cangelosi, in Proceedings of the 21st International Society for Music Information Retrieval (ISMIR) conference, pp. 310-317, 2020.
Article | Code | Poster | SlidesI received a PhD in Machine Learning from the University of Manchester, under the supervision of Prof. Angelo Cangelosi (Machine Learning and Robotics), and Dr. Eduardo Coutinho (Applied Music Research Lab). My dissertation, "Structural complexity in music modelling and generation with deep neural networks" focused on the automatic evaluation of Generative Models in regard to their ability to compose music with realistic structure.
Jan 2024 - Now | Research Associate | University of Manchester, S+T+ARTS MUSAE project |
May 2021 - 2023 | Research Associate | King's College London (Distributed AI group), under the EU H2020 Polifonia project |
2019 - Now | Honorary Researcher | University of Liverpool (AMLab): Personalised music recommendation for mood regulation |
2018 - 2021 | PhD in Machine Learning | University of Manchester (ELLIS unit), Machine Learning and Robotics (MLR) group |
2017 - 2018 | Research Assistant | University of Camerino: Multi-agent systems for traffic modelling and simulation |
2014 - 2016 | MSc in Computer Science | Reykjavik University, University of Camerino (Double Degree) |
I am always happy to supervise students eager to embark on Music AI research projects and internships. Feel free to reach out if you have a keen interest in exploring any research topic from above, or if you have a specific project proposal to discuss. I really value motivation, a critical mindset, and perseverance.
Connect with me via email at jacodb@liverpool.ac.uk.