Pedro Sarmento

Pedro Sarmento is a Research Fellow at Queen Mary University of London's School of Electronic Engineering and Computer Science. His research focuses on Sound and Music Computing, leveraging deep learning and AI techniques for symbolic music generation, particularly in guitar tablature formats. He leads projects like Guitar-Oriented Neural Music Generation, exploring prescriptive notation in fretted instruments using datasets like dadaGP and GigaMIDI.

His work integrates transformer models for tasks such as emotion-conditioned music generation, style transfer, and live coding performances. Notable applications include mapping smart city sensor data (e.g., air quality) to musical outputs. Collaborations span music informatics, interdisciplinary projects in progressive metal composition, and AI ethics in creative processes.

Research highlights include conditional music generation, guitarist style modeling, and dataset development for expressive music performance analysis. Pedro contributes to the Centre for Digital Music (C4DM) and actively publishes in AI-driven music technology, bridging computational methods with artistic creativity.