I am a PhD candidate in the Department of Information Science at Cornell University, and a member of the Culturally Embedded Computing research group.
I study how data scientists approach, organize, analyze, and visualize the world with and through data structures, computational algorithms, and statistical techniques. In my work, I am particularly interested in the oft-invisible and under-articulated forms of human work constituting data science learning, research, and practice. I ask questions such as: what forms of human and technical work constitute data science, how do data scientists situate and evaluate data science results to make them meaningful in computational, business, and social contexts, etc. I study such question ethnographically in the context of data science learning environments as well as corporate data science teams.
Research Interests: Critical Data Studies, Data Science, Machine Learning, Data Science Learning and Professionalization, Sociology of Algorithms, Data Visualization, and Digital Humanities.