Cyrus Vahidi

Cyrus Vahidi is a researcher affiliated with the School of Electronic Engineering and Computer Science at Queen Mary University of London. His PhD project focuses on perceptual end-to-end learning for music understanding, exploring synergies between sparse audio signal representation, psychoacoustics, and deep learning. He investigates novel neural network architectures to emulate human auditory tasks like event detection and source separation, with applications in music production and audio transformation.

Teaching responsibilities include contributing to undergraduate and postgraduate modules such as Digital Signal Processing and Fundamentals of DSP, covering topics like sampling theory, filter design, and practical DSP applications. His research interests span generative modeling, timbre analysis, and computational auditory perception.

Current work emphasizes adaptive perceptual audio representations and end-to-end learning techniques, leveraging psychoacoustic principles for industry-relevant audio processing tasks.