Prof Mark Sandler

Mark Sandler
FREng, FIEEE, FIET, FAES

Professor of Signal Processing
Director of The Centre for Digital Music

School of Electronic Engineering and Computer Science
Queen Mary University of London
ORCID Scopus Google Scholar LinkedIn

Research

Music and Audio Signal Processing, Music Informatics, Mathematics of Deep Learning, Sound Synthesis, Musical Source Separation, AI and Creativity

Interests

Digital Signal Processing, Machine Learning and Deep Learning especially for Audio and Music. Topics include: Digital Music & Digital Audio; Audio Segmentation; Harmonic Analysis; Source Separation; Neural Audio; Audio Synthesis; Physics-informed Neural Networks.

In the past I have done research in many areas in audio and music. These include: fractal and chaotic audio modelling, digital audio power amplification, sigma-delta modulation (SDM) for Digital to Analogue Conversion (DACs), immersive and surround sound (including ambisonic to binaural conversion, perceptual evaluation), high order all-pole modelling of musical instruments, drum synthesis, efficient architectures for EQ, music recommendation and play listing, key and chord analysis, vocal imitation for browsing of sound sample collections, linked data for music informatics and music cultural heritage.

I also spent around 10 years working in Computer Vision. Topics included several multi-processor architectures for high throughput processing, edge detection and thinning, Hough Transform for parametric detection of curves and lines in images, optical flow techniques.