I am a machine learning researcher with experience in data pipelines and distributed execution frameworks.
My research focuses on machine learning algorithms with algebraic, geometric, or probabilistic constraints. I led research that extended robust PCA to cyclic group algebras, matrix completion to abelian group algebras, and deep learning to arbitrary algebras. I also developed a model-based PCA method with an extensible library of error covariance structures.
I hold a PhD from Goldsmiths, University of London, where I developed computational models of music cognition.