Alessandro Ragano

Alessandro Ragano is a Postdoctoral Researcher at the Insight Centre for Data Analytics, where he has been investigating Quality of Experience (QoE) aspects of audio archives and developing data-driven approaches for QoE estimation and audio restoration using deep learning since 2018.

• Education:
  • MSc in Computer Science and Engineering from Politecnico di Milano (Italy)
  • BSc in Computer Engineering from Università Degli Studi di Salerno (Italy)

His research integrates machine learning, audio signal processing, and multimedia quality assessment to improve speech enhancement, audio restoration, and perceptual modeling. Recent trends in his publications focus on self-supervised learning, objective quality metrics, and audio dataset generation with applications in speech separation, music representation, and audio inpainting.

He actively contributes to open-source tools like Binamix and AQP for audio research and quality evaluation.