Machine learning · DDSP
Guitar Effect Reconstruction
Developed a DDSP-based model to reconstruct delay-line-based guitar effects, exploring machine learning approaches to audio effect modeling.
View research projectMusic Technologist · Music Producer · Jazz Pianist
Ziwen Ren (Kevin) explores digital signal processing and machine learning for music and audio. His work spans guitar effect modeling, audio software development, and composition across jazz, electronic music, and electric jazz.
Machine learning · DDSP
Developed a DDSP-based model to reconstruct delay-line-based guitar effects, exploring machine learning approaches to audio effect modeling.
View research projectC++ · JUCE
Implemented a convolution reverb using C++ and JUCE.
View reverb projectMax/MSP · Sound synthesis
Built an additive synthesizer in Max/MSP for exploring jazz harmony through sound synthesis.
View synthesizer projectAlongside his technical work, Kevin composes and performs across jazz and electronic music. His studies at Berklee included small-ensemble jazz piano, big-band composition, sound synthesis, mixing, and EDM production.
Listen to his musicA cinematic electronic piece built around expansive timbres, rhythmic momentum, and a sense of movement through an imagined landscape.
Originally from Wenzhou, China, Kevin studied classical piano before pursuing jazz performance and composition at Berklee College of Music. His curiosity about the structures behind harmony and sound led him to transfer to Electronic Production and Design, where he focused on digital signal processing and audio programming.
He developed synthesis and effects projects using Max/MSP, Csound, and C++. During his final year at Berklee, he explored several approaches to guitar effect reconstruction before building a model based on DDSP.
His ongoing interests center on audio machine learning and creative music tools. He aims to connect technical research with the practical needs of musicians and producers.