Music & AI
My research extends into the intersection of artificial intelligence and music, exploring how machine learning can understand, generate, and collaborate with human creativity.
Book
Deep and Shallow: Machine Learning in Music and Audio
Chapman and Hall/CRC, 2023
Publications
ImproVision: Visual Communication and Human-Computer Interactions for Musical Creativity
Leonardo, 2025
ImproVision Equilibrium: Toward Multimodal Musical Human-Machine Interaction
Transactions of the International Society for Music Information Retrieval, 2025
Creativity and Visual Communication from Machine to Musician: Sharing a Score through a Robotic Camera
International Conference on ArtsIT, Interactivity and Game Creation, 2024
Spectrogram-Based Deep Learning for Flute Audition Assessment and Intelligent Feedback
IEEE International Symposium on Multimedia (ISM), 2023
Bridging Subjectivity and Objectivity in Evaluation of Machine-Generated Jazz Music: A Multimetric Approach
IEEE International Symposium on Multimedia (ISM), 2023
Comparative Assessment of Markov Models and Recurrent Neural Networks for Jazz Music Generation
arXiv preprint, 2023
Quantifying Repetition in Symbolic Music Using Lempel-Ziv Compression
IEEE Annual Ubiquitous Computing, Electronics & Mobile Conference, 2023
Restoring Eye Contact to the Virtual Classroom with Machine Learning
International Conference on Computer Supported Education (CSME), 2021
Together With Classical: The Intersection of AI & Music
Together With Classical series
Teaching
CSE 190: Machine Learning for Music and Audio Previously taught at UC San Diego, covering machine learning techniques applied to music information retrieval, audio signal processing, and generative models.
Creative Practice
In addition to my research, I am a practicing conductor and orchestrator and love making music with inclusive ensembles.