About me

My name is Furkan Yesiler. I am currently an Early Stage Researcher / Ph.D. candidate at Music Technology Group, Pompeu Fabra University, specializing in research on machine learning for audio and music applications with a focus on contrastive and self-supervised learning.

My Ph.D. research focuses on building data-driven musical version identification systems for industry-scale use cases and is supported by the MIP-Frontiers project (MSCA Grant No: 765068). During my research career, I have worked on various topics around music informatics including musical version identification, audio fingerprinting, chord recognition, and singing voice analysis. My current research interests include applications of audio/music similarity (e.g., retrieval, recommendation), and waveform-based music processing and generation.

Before starting my Ph.D. journey, I received my MSc. degree in sound and music computing also from Pompeu Fabra University, and my two BSc. degrees summa cum laude in computer engineering and industrial engineering from Koc University, Istanbul.