I am inspired by music technology both from engineering and artistic points of view. I am interested in how it can help us in development of novel ways of interacting with music, providing tools for its creation, and potentially challenging our understanding of it.
I am a post-doctoral researcher at the Music Technology Group of Pompeu Fabra University in Barcelona, Spain. I work on audio analysis and semantic annotation of large-scale music collections using signal processing and machine learning techniques.
I develop and maintain Essentia, an open-source C++/Python library for audio analysis and audio-based music information retrieval. My work includes design and implementation of new audio analysis algorithms, management and documentation of the project.
I am also one of the coordinators of AcousticBrainz, an open database of music features extracted from audio, bridging the gap between audio analysis technology and the wider open music metadata community.
I graduated from Moscow State University with Diploma in Applied Math and Informatics in 2006 and received my Ph.D. in Information, Communication and Audiovisual Technologies at the Music Technology Group of Pompeu Fabra University in 2013. My PhD thesis was focused on music recommendation systems using audio analysis and metadata (read my thesis here).