About

Every degree I hold is in music. Everything I've done for the last decade is machine learning. The distance between those two sentences is the story.

The score

I trained as a composer: a Bachelor of Music at the University of the Pacific, an MFA in Electronic Music and Recording Media at Mills College, and a Doctor of Musical Arts in composition at the University of Colorado, Boulder. The music that interested me most was the kind that needed software to exist — live coding, network music, multichannel electronics — so I spent those years performing with the band Glitch Lich at algoraves and festivals across North America, Europe, and Asia, and building the frameworks we performed with. After the doctorate I moved to Shanghai, teaching composition and theory at the FaceArt Institute of Music and performing throughout China, Germany, and beyond. Those years are catalogued in the performance archive.

The signal

In 2015 I joined Amper Music in New York as Chief Scientist — the sole initial engineer, turning minimal sketches into a production generative-music platform that became one of the highest-quality on-demand commercial music generators in the world. That work produced three granted U.S. patents and, eventually, an acquisition by Shutterstock, where I became Director of AI Research: founding member of the Shutterstock.AI business unit, shipping machine-listening and semantic search into production. From there, Director of Data Science at Bluecore, leading ML teams across New York and India through production model launches and a Black Friday at full load.

Since 2023 I've worked where I'm most useful: the boundary between people who build AI and people who need to use it. As Lead AI Instructor at NYC Data Science Academy and an author and instructor for Pluralsight, I've delivered well over a hundred hours of curriculum in Python, machine learning, and generative AI to engineers and analysts at companies including KPMG, Intuit, and Salesforce. As an independent consultant I build applied-AI systems — NLP pipelines for investment research, energy price forecasting, generative-AI product prototypes.

The through-line

The move from composition to machine learning looks like a career change, but it never felt like one. Computer music is a technical discipline wearing an artistic costume: my composition work was already software engineering, signal processing, and systems design, just aimed at loudspeakers. When Amper needed someone who understood both how music works and how to build production systems, the "unusual" background was exactly the qualification. The real skill underneath — entering an unfamiliar, technically demanding domain and becoming productive fast, without waiting for credentials — is the one I've used at every step since, and it's the one I try hardest to teach.