Hegel Pedroza (1991, Mexico City) is a Mexican guitarist, composer, and researcher specializing in music technology. He holds a Bachelor’s degree in Contemporary Popular Music Composition from the Academia de Música Fermatta (2012) and a Master’s degree in Music Technology from the National Autonomous University of Mexico (UNAM, 2023). He has also completed additional studies in sound art, technology, and artistic research.

He has held full-time teaching positions at the Autonomous University of the State of Mexico and at the Academia de Música Fermatta, and has served as an adjunct professor at Tecnológico de Monterrey and SAE Institute Mexico. He is currently a Full-Time Research Professor at the Lerma Campus of the Universidad Autónoma Metropolitana (UAM), where he combines his academic work with musical activity and multimedia project consulting.

His creative work encompasses composition, musical performance, and digital art. As a composer, he has written music for advertising, short films, and a feature-length documentary; his concert works have also been recognized through international calls and collaborations in Spain, the United States, and Germany. As a guitarist, he leads a contemporary jazz trio that has performed at major festivals in Mexico.

As a digital artist, his work has been presented in venues such as the compilation album Homenaje a Aram Slobodian (Spanish Electroacoustic Music Association, 2013); the exhibition Cortázar en Casa (Casa América de Catalunya, 2014); the group exhibition Getxo Arte (Getxo City Council, 2014); the Central Emerging Art Festival (AECID, El Salvador, 2019); and the exhibitions Creaciones con algoritmos: visualización y sonificación de datos (2020) and Geometrías Sensibles (2021) at the Centro de Cultura Digital. He has also presented work in the solo exhibition Trípticos.

As a researcher, his work focuses on the development of music technologies applied to the guitar and on artificial intelligence, with particular emphasis on dataset design for deep learning models aimed at transcription and performance analysis of guitar playing.