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.

  • Ph.D. (Ongoing)

    Information Science

    Cornell University, USA

  • M.Sc. Research

    Science & Technology Studies

    Maastricht University, NL

  • B.Tech.

    Information & Communication Technology

    DA-IICT, India

Recent Updates

  •    I am currently working as a machine learning intern at a mid-size (2.5k-5k employees) online e-commerce and media company on the West Coast, simultaneously conducting ethnographic research on practices constituting and constitutive of data science and analytics in this corporate setting. (June 2017 – ongoing).
  •    My CSCW 2017 Best Paper on Data Vision with co-author Steve Jackson got a write-up at Cornell University’s Department of Information Science’s webpage. Here is the link. (April, 2017)