degredations

Slow, repetitive, contemplative, and noisy. Repeatedly-applied neural reconstructions fail slowly and imperceptibly as feature space is explored.

Nicholas Shaheed is a composer, software maker, electronic musician, and researcher. His work, often contemplative and slowly-shifting, engages with intertwining textures, feedback, process, and interactive software systems.

As an artist and researcher, his work intersects with audiovisual performance, building software tools, and live performance. From transforming a viola d'amore into a crowd of hushed murmurs to creating a group improvisational system for intercepting degrading feedback loops, his work often uses machine learning as a tool for real-time exploration of material.

His work has been presented at conferences such as NIME, NYCEMF, and SEAMUS, and he has been a fellow at Stochastic Labs and the Norfolk New Music Workshop. He is currently a PhD candidate in Computer Based Music Theory and Acoustics at Stanford's Center for Computer Research in Music and Acoustics (CCRMA).