About Me




– apr 14: speaking about “algorithmic ethics in crime analysis” at the social and cultural sciences department colloquium at Marquette.

– apr 1: paper on geographical biases in cs education in Wisconsin with Dennis Brylow and Heather Bort accepted to ITICSE18.

– mar 30: speaking about “algorithmic ethics in crime analysis” at the HCC department colloquium at IUPUI.

I am an assistant professor at the Department of Mathematics, Statistics and Computer Science at Marquette University. I lead Data Science efforts and participate in the Cognitive Science program. Previously, I received a PhD from Cornell University under Steve Wicker and a MS from the Indian Statistical Institute under BS Daya Sagar.

My current research interests cut across human computer interaction, computational social scienceictd and privacy. My work generally focuses on marginalized and developing contexts in computing. Some people have taken to calling this as data science 4 social good recently.

Currently, I am interested in the following broad (and often intersecting) themes in my research:

  • the networked dynamics of privacy: There are many different aspects of  privacy in social networks e.g. surveillance, anonymity, deception, non-use, impression management etc. How can we examine and explain their dynamics?
  • human-centered algorithmic ethics: We all do data analysis in different ways everyday. Algorithms and data increasingly govern many facets of our daily lives. How do we (re) imagine humans in the algorithm-data loop? Is there a way in which we can do data analysis better and more transparent ?
  • privacy in non-WEIRD contexts: There have been many theories of privacy developed in WEIRD (Western Educated Industrialized Rich Democratic) contexts over the years. How do we think about theorizing and empirically probing theories of privacy and its variegated aspects in non-WEIRD contexts with respect to computing technologies?

My academic philosophy (or why I joined Marquette):

  • I strongly believe that computer scientists should have a rigorous liberal arts background. Marquette’s Jesuit history fused with a very unique common core accomplishes this for every student. I get to contribute to this by creating my own cultivar of our data science major.
  • Our graduate program in computational sciences is a very unique doctoral degree that enables students to model, analyze and build systems from complex datasets by merging mathematics, statistics and computer science. This is an excellent, technically rigorous sandbox for training and working with the next generation of computational social scientists.

I am always looking for motivated students at all levels (BS, MS, PhD) to work with me. If you are interested, please read this and get in touch. This is my cv, my github and my infrequently updated blog.

If you want to get in touch please feel free to email me at shion [dot] guha [at] marquette [dot] edu.