Javier Nistal

Javier Nistal is a researcher on artificial intelligence for music and audio applications, specializing in deep generative models and sound synthesis. He holds a degree in Telecommunications Engineering from the Technical School of Madrid (UPM), a master’s in Sound and Music Computing from the Music Technology Group (MTG) in Barcelona, and a PhD from Télécom IP Paris.

As an active contributor to the field, Javier has published at leading music conferences such as ISMIR, NeurIPS, and ICML, advancing the state of AI for music. His work focuses on creating intuitive, controllable tools that enhance human-machine collaboration, making music technology more accessible and transformative for artists and producers alike.