My name is Oriol Colomé, and I am a musician and a music scientist.
A bit about myself: I’ve spent over a decade making a living from and for this wiggly air and cognitive phenomenon we call music. While my core education is music-based, I’ve been shifting to the music tech space in the past few years, where I am developing my career. I enjoy working with all kinds of folks—musicians, industry pros, academics, product people, you name it.
I have proven experience in almost all of the stages of the music production pipeline: leading and developing teams on the creative, product, and business sides, aiming to build strong relationships with stakeholders. This helps me make informed decisions to support business growth.
I like to think of myself as a jack of all trades. Although I have a more substantial musical background, I also have relevant experience in the product and tech side of the music business, which allows me to connect artistic and business needs: all things music.
My master's thesis at UPF's Music Technology Group (MTG), in collaboration with Epidemic Sound AB, explored novel approaches to music structure analysis using self-supervised deep neural networks. The work focused on learning sound-agnostic and content-sensitive music representations through contrastive learning and triplet networks.
