My research has been centered around a variety of machine learning methods and applications, the common thread across which has been to identify and utilize structure when it exists. I have worked on understanding and applying quantum-inspired probabilistic models for sequential data. Recently, I worked on incorporating geometric information about data spaces into sampling algorithms. Currently, I am interested in policy composition techniques in multi-objective decision making problems wherein complex objectives are broken down into multiple manageable components.