My PhD thesis concerns separating the audio corresponding to the instruments in an orchestral music mixture. This allows for interesting applications such as re-creating the experience of the concert in virtual reality applications.
My research interests span a diverse range of topics: artificial intelligence, music information retrieval, real-time interaction, ethnomusicology, and signal processing. I participated in interdisciplinary projects, such as Shake-it and PHENICX.
Check out my latest deep learning repository in python. I am committed to the principles of research reproducibility. Most of the code is made available through github, along with links to the dataset and instructions on how to replicate experiments.