Ph.D. candidate in Information Science at Cornell University.

I study data science as a social, situated, and collaborative practice – focusing on the oft-invisible human work essential in getting data, algorithms, and models to work together.

Also a member of the Culturally Embedded Computing (CEMCOM) and Artificial Intelligence, Policy, and Practice (AIPP) research groups at Cornell University.

Ph.D. Candidate (Present)
Information Science

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

Bachelor of Technology (2010)
Information Technology

Latest News

  •    FAT* 2019 paper featured in MIT Technology Review’s ‘The Algorithm’ newsletter edition. The focus of this edition was on the difficulty of assessing algorithmic bias. Check it out here.
  •    Participated in the Social Science Research Council’s (SSRC) special seminar on “Mechanical Rules before Machines: Rules and Paradigms” led by Lorraine Daston.
  •    The news publication Cornell Chronicle 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.
  •    FAT* 2019 paper – Problem Formulation and Fairness – featured in the news publication SiliconANGLE. Check it out here.