My research interests lie in the area of machine learning and analysis of time-based data, music representation, and e-learning applications. I am particularly interested in Deep Learning methods for combining and integrating signals with symbolic information and logic.
I was the Principal Investigator of
I was the Co-Investigator in
I was a member of the MPEG Ad Hoc Group on Symbolic Music Representation, where we developed the SMR standard for music notation and structural information within MPEG-4.
I was coordinator of the MUSITECH project which provides a platform for musical applications.
I was a consultant to the NEUMES project at Harvard University.
In my doctoral dissertation I developed the Integrated Segmentation and Similarity Model for music analysis.
I am co-author of the music education software "Computer Courses in Music - Ear Training" which has been publishd by Schott.
In my mster's thesis I developped a grammer for chord sequences in jazz (see Publications for a paper on it).