– dec 1: very excited to receive the Facebook Computational Social Science Methodology grant 2018.
– nov 8: speaking about “algorithmic ethics in crime analysis” at the Department of Computer Science Seminar at University of Illinois Chicago.
– oct 15: hiring Northwestern Mutual postdoctoral fellow starting Spring 2019!
I am an assistant professor at the Department of Mathematics, Statistics and Computer Science at Marquette University. I also hold an administrative position as the Director of Data Science 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 science, ictd and privacy. I often work with various marginalized and developing populations. My research is (and has been) supported by the following:
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:
- 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.
If you want to get in touch please feel free to email me at shion [dot] guha [at] marquette [dot] edu.