Estefanía Cano holds degrees in Electronic Engineering (B.Sc) from Universidad Pontificia Bolivariana and Music-Saxophone Performance (B.A) from Universidad de Antioquia in Medellín, Colombia.
After finishing her engineering studies with a project that explored the use of Wavelet Transform to monitor fetal heart signals, she moved to the United States where she completed her master degree (M.Sc) in Music Engineering at the University of Miami with a thesis titled "Melody line detection and sound separation in classical saxophone recordings." During her time at the University of Miami, she worked as a research assistant in the Image Processing Laboratory in projects dealing with underwater imaging and sonar technologies.
In 2009, she joined the Semantic Music Technologies group at the Fraunhofer Institute for Digital Media Technology IDMT to pursue her PhD. She obtained her doctoral degree in 2014 with a dissertation entitled "Pitch-informed solo and accompaniment separation". As a research scientist at Fraunhofer IDMT, she has been involved in projects related to the development of music learning games, instrument classification, pitch detection, and sound separation among other music information retrieval topics.
Her research mainly focuses on sound source separation, specially dealing with pitch-informed separation and harmonic/percussive separation. She is also interested in the analysis and modeling of musical instrument sounds, the use of phase information for information retrieval, musical instrument classification, and the use of music information retrieval techniques in musicological analysis.