I am a PhD candidate in the Department of Information Science at Cornell University with a minor in Science & Technology Studies.

 

I study how people organize, analyze, and visualize the world with and through large-scale datasets, computational algorithms, and specialized statistical techniques. My research is situated at the intersection of Information Science, Computer Science, and Science & Technology Studies. In my work, I ask questions such as: what forms of human work and decisions constitute data analyses, how do we and should we evaluate and contextualize data analytic results, how can we know when data analysis has or hasn’t worked, how can we better communicate data analytic results and processes to experts and non-experts alike, how can we build better systems to identify and accommodate a more human-centric view of data analysis?

 

Research Interests: Critical Data Studies, Machine Learning, Critical Design, Digital Humanities, Sociology of Algorithms, and Ethics of Data Visualizations.

  • Ph.D. (Ongoing)

    Information Science

    Cornell University, USA

  • M.Sc. Research

    STS

    Maastricht University, NL

  • B.Tech.

    ICT Engineering

    DA-IICT, India

Recent Updates

  •    Delivering a lecture – “It’s Data Science: Exploring the Human Face of Data Analysis” – at the Department of Architecture, Art, and Planning at Cornell University for ARCH 3819 – Design Culture and Practices in the Digital Era. (December, 2016)
  •    Giving a presentation at the 4S/EASST conference in Barcelona, Spain. It is in the Critical Data Studies track and is titled “Data Pedagogy: Learning to Make Sense of Algorithmic Numbers” (September, 2016)