Néstor Nápoles López

Néstor Nápoles López

PhD in Music Technology

About me

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.

Interests
  • Computational Music Theory
  • Music Information Retrieval
  • Deep Learning
  • Music gamification
Education
  • 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

Other publications

(2020). Harmonic Reductions As a Strategy for Creative Data Augmentation. In ISMIR 2020.

PDF Cite Poster ISMIR Website

(2020). Do-Re-Myth: An Ear Training Game. In COBS.

Cite Code Project Video

(2019). Musical Tic-Tac-Toe. In LMusTP 2019.

Cite

(2019). Dandelot - Reading Music as a Game. In LMUSTP 2019.

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