My work focuses on building creative and technical audio systems for interactive media. I design sound effects, create procedural audio tools, and develop workflows for analyzing, organizing, and generating sound. My recent work uses machine learning as a practical tool for audio, making sound systems more adaptive and responsive while keeping creative control at the center.
I am currently completing a Master of Music in Music Technology at New York University, with a focus on sound design and audio programming. I also hold a Bachelor of Arts in Music Management and Psychology, with minors in Music and Film Studies. This background has given me experience across several areas of business, media, and audio, which helps me approach my work from both a technical and creative perspective.
My thesis explores machine-learning–assisted sound design through a procedural explosion system built in Max/MSP. Using audio embeddings to organize and trigger sound material, the system allows real-time control over how sound effects are constructed and performed.
See the thesis page for GitHub, technical documentation, and implementation details:
Python, JavaScript, Max/MSP
Pro Tools, Adobe Audition, Ableton Live
Premiere Pro, Final Cut Pro
Unreal Game Engine, Wwise