My interests lie at the intersection of machine learning (ML) research and practical applications. My academic interests are in ambient data collection and just-in-time adaptive interventions, with applications in nutrition and dietary habits. During my time in industry, I have contributed to ML infrastructure and models for a variety of Fortune 100 companies. I have developed models for ML accelerated drug design, created algorithms for low-resource wearable sensors, and optimized smart electric grids using advanced modeling methods. My goal is to continue leveraging ML to improve efficiency and functionality in any sector doing interesting and valuable work.