Dr Emmanouil Benetos is Senior Lecturer at the School of Electronic Engineering and Computer Science of Queen Mary University of London (QMUL). At QMUL, he is member of the Centre for Digital Music, Centre for Intelligent Sensing, Institute of Applied Data Sciences ,and Digital Environment Research Institute, and he is co-leading the School's Machine Listening Lab. In 2015-2020, he was Royal Academy of Engineering Research Fellow on machine learning methods for audio analysis. His main research topic is computational audio analysis, also referred to as machine listening or computer audition - applied to music, urban, everyday and nature sounds. He has been principal- and co-investigator for several audio-related funded research projects on topics related to sound scene analysis, music information retrieval, and digital musicology. He is also investigator for the large doctoral training projects MIP-Frontiers the UKRI Centre for Doctoral Training in Artificial Intelligence and Music (AIM).
Dr Benetos' research at The Alan Turing Institute focuses on audio data science, specifically towards advancing research on models, algorithms and practices for making sense of complex audio data in real-world multi-source environments. At the Turing he is member of the Turing Skills Group and the Humanities and Data Science and Robust Machine Learning special interest groups. His research covers two application domains: sound monitoring in urban & domestic environments and automatic analysis of music audio recordings in noisy environments. A major part of his Turing Fellowship will focus on shaping standards and policy for privacy-preserving audio analysis methods and on identifying ethical issues and implications related to access and (re-)use of audio data.