I am a PhD candidate in the Department of Information Science at Cornell University. I am a member of Cornell University’s Culturally Embedded Computing (CEMCOM) research group and of Cornell University’s initiative on Artificial Intelligence, Policy, and Practice (AIPP).


I study how data scientists approach, organize, analyze, and visualize the world with and through data structures, computational algorithms, and statistical techniques. I am particularly interested in the oft-invisible and under-articulated forms of human work constituting data science learning, research, and practice. Instances of such work range from the conceptualization of data-driven questions and pre-processing of datasets to translating between corporate values and computational goals and the work of managing corporate data science projects.


Research Interests: Critical Data Studies, Data Science, Machine Learning, Data Science Ethics and Policy, Sociology of Algorithms, Data Visualization, and Digital Humanities.

Ph.D. Candidate (Present)
Information Science

M.Sc. Research (2012)
Science & Technology Studies

Bachelor of Technology (2010)
Information & Communication Technology

Recent Updates

  •    Our CSCW paper – titled Trust in Data Science: Collaboration, Translation, and Accountability in Corporate Data Science Projects – received the Best Paper Award at CSCW 2018.
  •    Solon Barocas and I presented our work on the relationship between normative implications and problem formulation in data science work to the Artificial Intelligence, Policy, and Practice research group at Cornell University (September 2018).
  •    Presented a paper – The Stakes are High: But, do we know what they look like? – at the Lives of Data 2.0 SARAI Workshop at the Center for the Study of Developing Societies (CSDS) in New Delhi, India. (January, 2018)