Chris Winnard

Chris Winnard is a PhD Student at Queen Mary University of London's School of Electronic Engineering and Computer Science, affiliated with the Centre for Digital Music (C4DM). His research focuses on measuring 'music interestingness' in the brain using Ear-EEG technology to analyze neural responses during music listening. This interdisciplinary project combines music cognition, signal processing, and machine learning to develop personalized music recommendations and explore brain stimulation through music.

His work involves collecting EEG data from healthy subjects while listening to music, applying machine learning algorithms (e.g., deep neural networks) to model interestingness. Collaborations include the Centre for Ear-EEG at Aarhus University. Research themes include personalization of models, multimodal integration of music features (e.g., melody, genre) with EEG signals, and advancing brain-computer interface applications in music technology.

No scientific awards or grants are explicitly mentioned, but the project emphasizes cutting-edge methods in neural signal analysis and music technology.

Chris’s research contributes to understanding individual music perception and has potential applications in adaptive music systems and neuroscientific studies.