I am a sixth-year Ph.D. candidate in the Department of Information Science at Cornell University.

At Cornell, I am also a member of the Culturally Embedded Computing (CEMCOM) research group and of Cornell University’s initiative on Artificial Intelligence, Policy, and Practice (AIPP).

I study data science as a social and situated practice – focusing on the oft-invisible human work essential in getting data, algorithms, and numbers to produce results ‘all by themselves.’ Examples of such work include: translating high-level goals into data-driven problems, improvising on algorithmic methods and mechanical rules in the face of empirical messiness, and establishing the trustworthiness of data, algorithms, and models in data science projects. I study such forms of work ethnographically in the context of academic and corporate data science.

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

Recent Updates

  •    Cornell University did a news write-up on our CSCW 2018 paper – Trust in Data Science: Collaboration, Translation, and Accountability in Corporate Data Science Projects. Read more about it here.

Ph.D. Candidate (Present)
Information Science

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

Bachelor of Technology (2010)
Information & Communication Technology