I’m passionate about using modern technologies to learn, understand, and create music.
My research focuses on symbolic music processing, computational music theory, and deep learning, including my PhD work on deep learning models for automatic Roman numeral analysis.
I’ve worked at Intel, Avid, and now serve as Principal Machine Learning Scientist at Musical AI.
PhD in Music Technology, 2022
McGill University, Montréal
MSc in Sound and Music Computing, 2017
Universitat Pompeu Fabra, Barcelona
Licenciatura en Informática, 2013
Universidad de Guadalajara, México