Here you can find more information about what I do. For now, here's my short bio.
I'm a Lecturer in Digital Media at Queen Mary University of London, working at the Centre for Digital Music (C4DM), School of Electronic Engineering and Computer Science. I received a BSc degree at Kandó Kálmán College of Electrical Engineering, now part of the Óbuda technical University. I received an MSc degree at Queen Mary University of London, and a subsequent PhD degree in 2012 at the same institution. My doctoral thesis titled “Semantic Audio Analysis—Utilities and Applications” describes novel applications of semantic audio analysis, Semantic Web technologies and ontology-based information management in Music Information Retrieval as well as in intelligent audio production tools. My main research interest includes the development of semantic audio technologies and their applications to creative music production, ontology-based information management, audio signal processing and machine learning, Semantic Web, linked data, and knowledge-based reasoning. I developed online tools for semantic audio analysis which seamlessly integrate with Semantic Web technologies. I proposed a novel automatic ontology generation system for web-based audio signal processing applications in collaborative work. I worked with BBC Research and Development to build mood-based music recommendation systems in the TSB funded Making Musical Mood Metadata project, and collaborated with researchers from the Finnish Centre of Excellence in Interdisciplinary Music Research on creating semantic mood models for music. I collaborated with the French vocal group VoXP to create the Mood Conductor system that enables audiences to interact with performers in live improvised music using a Psychological model of mood and mobile technology. I was papers co-chair and led the local organising committee of the 53rd AES International conference on Semantic Audio, co-organised by Queen Mary University and the Fraunhofer Institute. I am Co-Investigator of several collaborative research projects, and a member of the AES, ACM and BCS.