About Me

There are 2 types of people: those who hear music and think about dancing, and those who think about the mathematical patterns behind it. Needless to say, I couldn’t care less about dancing.

I’m fascinated by how music, mathematics, and machine learning intersect. I enjoy exploring how we can teach machines to understand the mathematical patterns in music, and how we can use technology to understand, create, and transform musical experiences. I believe in building solutions that are not merely technically sophisticated, but also transparent and meaningful to the people who use them.

With 5 years of experience working on machine learning projects across various industries, I’ve picked up knowledge of software engineering practices, end-to-end ML in Python, working with databases, and exploring LLMs. I’ve built practical solutions that have saved thousands of manual work hours across industries, and hope to bring my technical expertise into the world of music. I recently attained a Masters in Sound and Music Computing, which has equipped me with knowledge of music and audio processing methods. Along this journey, I’ve had fun building all sorts of interesting projects - from systems that can generate music (which have been described as “Bach on Drugs”) to creative multimodel systems.

Based in London and always up for a good chat about music, machine learning, or the occasional philosophical debate about whether computers can truly achieve creative autonomy. If you’re interested in collaborating on projects where music and tech collide, let’s connect!