I develop methods, applications, and tools to enhance human learning and behavior through machine learning. My research includes statistical and computational methods for modeling complex user behavior from massive and complex data; developing algorithms for adaptation and personalization; and creating software to support other researchers in implementing these methods across domains.
My work has addressed questions relevant to many domains, including high-dimensional model selection, social network-augmented classification, next-action recommendation, computer vision, generative modeling, and reproducible research with massive private datasets. To date, my research has evaluated diverse settings, including Massive Open Online Courses (MOOCs) and traditional higher education institutions, digital games, large government datasets, and single-cell electron microscopy imaging. The unifying theme of my research is to develop tools and methods for machine learning which drive real-world impact.
I am currently pursuing a PhD in computer science at the University of Washington's Paul G. Allen School of Computer Science & Engineering. Previously, I received a Master of Science in Applied Statistics and a Master of Science in Information from the University of Michigan.