Building differentiable audio systems at the intersection of signal processing and machine learning. Specialising in artificial reverberation, Feedback Delay Networks, and intelligent audio effects — based at the Centre for Digital Music.
I'm a PhD researcher at Queen Mary University of London, working within the Centre for Digital Music (C4DM) under the supervision of Prof. Joshua D. Reiss. Prior to my PhD, I spent 8 years at DiGiCo, developing professional audio systems and bridging engineering with live sound production.
My research focuses on making reverberation algorithms fully differentiable — enabling gradient-based optimisation of parameters that were previously hand-tuned or inaccessible to learning frameworks. The goal is to close the gap between the perceptual richness of convolution reverb and the parametric control of algorithmic approaches.
I'm currently finalising work on a differentiable Feedback Delay Network that clones target room impulse responses using gradient descent, with a novel parametric EQ approach that reduces filter complexity by over two-thirds without sacrificing accuracy.
Designing and optimising Feedback Delay Networks (FDNs) to synthesise realistic room acoustics with parametric control over frequency-dependent decay.
Making classical DSP building blocks — IIR filters, attenuation stages, delay lines — fully differentiable and compatible with gradient-based learning frameworks.
Applying inference-time optimisation and style transfer to control audio effects. Collaborating on differentiable compression, EQ, and reverberation for production contexts.
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Open to collaborations in differentiable DSP, audio effects research, and industry applications of intelligent audio processing.