Charilaos Papaioannou

I am passionate about interdisciplinary approaches that bridge engineering with insights from the social sciences to tackle complex problems. My primary research interests lie in Music Information Retrieval and Computational Musicology, where I develop deep learning models to transfer knowledge across musical traditions and uncover correlations between diverse music cultures. My goal is to create methodologies capable of analyzing world music, identifying similarities, and tracing influences across genres, instrumentation, and cultural contexts.

Beyond research, I value the synergy between rigorous scientific exploration and hands-on engineering. My experience across both industry and academia has equipped me with a strong combination of technical expertise, analytical thinking, and collaborative skills, which I bring to every project.

For more details, please refer to my detailed CV.

Research & Engineering Interests:

• Machine Learning
• Music Information Retrieval
• Computational Musicology
• Multimodal Learning
• Data Analysis
• Software Engineering