MixCards
Structured descriptions of sound scenes made of several overlapping sources.
My research explores how machines can make sense of music and the sounds around us. Together with my students, I develop signal processing and machine learning methods that help computers listen, interpret, and reason about sound.
I’m particularly interested in how sound connects with vision and language, what machine learning models actually understand about the acoustic world, and how we can make them more robust, interpretable, and reliable. Our work spans music information retrieval, environmental sound understanding, multimodal analysis and synthesis, and applications in accessibility and health.
Recent student-led projects.
Structured descriptions of sound scenes made of several overlapping sources.
Reasoning about sound from acoustic cues and evidence that can be checked.
Estimating how a room sounds from a point-cloud scan of the space.
How reliable the usual metrics are for binaural music source separation.
Visual sound source localization that learns from silence, noise, and off-screen sounds, not only from positive audio-visual pairs.
Self-supervised music representations that keep musical detail while separating the factors that shape it.
NYU Steinhardt Gabriel Carras Research Award for Promising Young Scholars.
Google Award for Inclusion Research
NYU Provost’s Postdoctoral Fellowship.
Best undergraduate thesis award, National Academy of Engineering of Uruguay.
Our work has been supported by the National Science Foundation, the National Institutes of Health, Google, Adobe, and NYU, in collaboration with colleagues at NYU and NJIT.
AI-supported audio captioning of non-speech information, with Mark Cartwright and Sooyeon Lee (NJIT).
Feasibility of a music listening intervention for mental health recovery after stroke, with Pablo Ripollés and Heidi Schambra.
Including Latin American culture in music information research.
Support for research in audio understanding.
AI-assisted tools for music therapy, and earlier work on sound captioning for accessibility.