Short Bio

My research focuses on novel, cutting-edge developments in statistical and deep learning models for the purposes of computational creativity. 

I aim to develop interpretable, controllable models that closely collaborate with humans in the creative process. Using my unique background as a music theorist and performer, my work on music generation models exemplifies the importance of domain knowledge in building simple models that work. My research in computational hierarchical music analysis is the first of its kind, aiming to understand organic musical structures.