I am a PhD candidate in the Department of Information Science at Cornell University with a minor in Science & Technology Studies.
I study how data scientists (learn to) 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 are involved in data science and analytics, how do people situate and evaluate data science results to make them meaningful in business, technical, and social contexts, etc. what are the relation between routine, creative, and expert data science work, etc. I study such question ethnographically in the context of data science classrooms/workshops as well as corporate data science teams.
Research Interests: Critical Data Studies, Machine Learning, Data Science, Data Visualization, Data Analytics, Sociology of Algorithms, Sociology of Visualization, Data Science Learning & Training, and Digital Humanities.