RCCHU Study Group on Iberian and Latin American Music (ILM)

Co-chairs: Alejandro L. Madrid (Walter W. Naumburg Professor of Music, Harvard University), and Álvaro Torrente (Professor of Music, Universidad Complutense de Madrid).

The ILM Study Group arises from a shared commitment to advancing transatlantic research on Iberian and Latin American music across all historical periods, through sustained collaboration between institutions in Spain, Latin America, and the United States. Bringing together faculty, graduate students, and early-career scholars from Harvard, Complutense, and other universities, the group seeks to foster long-term scholarly exchange, joint academic initiatives, and international mobility. One of its central goals is to create a supportive environment for emerging researchers working in musicology, ethnomusicology, and performance studies, encouraging interdisciplinary dialogue and mentoring across institutions.

The group explores the cultural, social, and political dimensions of musical practices in the Iberian and Latin American worlds, with particular attention to processes of circulation, hybridization, and identity formation. It promotes critical approaches that connect historical depth with contemporary relevance, engaging with themes such as colonial legacies, diasporic memory, and cultural resistance. A defining feature of the Study Group is its interdisciplinary orientation. It actively seeks dialogue with adjacent fields such as philology, philosophy, sociology, history, anthropology, and data science, fostering collaborative research that situates music within broader humanistic and scientific frameworks. By integrating methods and perspectives across disciplines, the group aims to develop innovative approaches to the study of music as both a cultural form and a site of knowledge production.  At the same time, the group serves as a platform for methodological innovation, advocating the use of Digital Humanities tools and the application of artificial intelligence in music research. From corpus analysis and pattern recognition to computational modeling and interactive learning environments, these technologies offer new possibilities for exploring music as a dynamic and transnational field of knowledge.