Full Professor of the Dept. of Information and Communication Technologies
Research interests: Audio Signal Processing, Sound and Music Computing, Music Information Retrieval, Computational Musicology
Research statement: "Since my PhD in Computer Music from Stanford University, obtained in 1989, my academic career has been moving and evolving within the field of music technology, always interested in the analysis, description, and synthesis of sound and music signals, always trying to find a balance between basic and applied research, and always exploring approaches from both scientific/technological and humanistic/artistic disciplines. The research that I currently supervise at the MTG is focused on the understanding of sound and music signals by combining signal processing and machine learning methods with semantic technologies. I emphasize the combination of data-driven methodologies, in which the development and use of large data collections is a fundamental aspect, with knowledge-driven approaches, in which domain knowledge of the problem to be addressed is needed. Within our publicly and privately funded projects, we work on practical problems such as music exploration and recommendation, classification of sounds, and music performance evaluation for music education. In all our research I emphasize open science, thus promoting open data, open software, and open access, but I am equally interested in exploiting our results with open innovation strategies to promote the social impact of our research."