I build audio machine learning systems that run outside the notebook. My work focuses on models for sound event detection, voice activity detection, and privacy-preserving audio, with particular attention to deployment on resource-constrained hardware.

For three years I was a Research Engineer at the University of Surrey (CVSSP), working on the EPSRC-funded AI for Sound project under Prof. Mark Plumbley. I published at ICASSP, WASPAA, ICWE, CHiME, Inter-Noise and SMC, built open-source tools, and supervised student projects. Before Surrey I spent four years at Ikatu developing embedded audio systems for Bang & Olufsen home automation products, which shaped how I think about the gap between research prototypes and devices that actually ship.

I work primarily in Python and PyTorch, and I am equally comfortable with microcontrollers, soldering irons, and signal processing from first principles. My background combines electrical engineering (Universidad de la República, Uruguay) and an MSc in Sound and Music Computing (Universitat Pompeu Fabra, Barcelona, 2021).

Currently based in Montevideo, Uruguay. Italian citizen with EU work authorization. Open to remote roles in LATAM/Europe and relocation within the EU.

Beyond my research work, I am an electronic music DJ and producer with over a decade of practice and formal musical training. Most of my interest in how machines listen started from how I listen myself.

Email: gabobibbo@gmail.com

Links: [ORCID] | [Scholar] | [Github] | [LinkedIn]