Upasana Dutta

Ph.D. student in Computer and Information Science @UPenn

Hi there! I'm Upasana.


I am a second-year Ph.D. student in Computer and Information Science at the University of Pennsylvania, working in the Penn Media Accountability Project group of the CSS Lab. I am very fortunate to be advised by Duncan Watts and Aaron Clauset (remotely). In 2022, I graduated with a Master's in Computer Science at the University of Colorado Boulder, where I was advised by Aaron Clauset and Dan Larremore
 
My research interests are primarily in computational social science, network science, and complex systems. Broadly, I am interested in developing computational models to understand what governs human behavior in social systems, such as consumption of news, gender and racial biases, team and opinion dynamics, echo chambers on social media, etc. I'm also interested in studying factors that lead to collective behavior, such as the spread of information, beliefs, norms, and diseases.
To know more about my academic activities, check out my Updates.

When I'm not working, I like practicing music, or trying out new recipes. And I love dogs! Thanks for stopping by :)

P.S. I am from India. My first name is pronounced like Oo-paa-sa-naa.

Publications


Scaling laws in empirical networks


Upasana Dutta, Alex Ray, Aaron Clauset

In preparation


Sampling random graphs with specified degree sequences


Upasana Dutta, Bailey K. Fosdick, Aaron Clauset

Preprint https://arxiv.org/abs/2105.12120


Analyzing Twitter Users’ Behavior Before and After Contact by Russia’s Internet Research Agency


Upasana Dutta*, Rhett Hanscom*, Jason Shuo Zhang, Richard Han, Tamara Lehman, Qin Lv, Shivakant Mishra

In Proceedings of the ACM on Human-Computer Interaction, CSCW. PACM-HCI 2021, https://doi.org/10.1145/3449164, (* equal contribution), (* equal contribution)

Projects


Underrepresentation of rural undergraduate students in CU Boulder


Worked with CU Boulder Office of Data Analytics and CU Rural Network to analyse how undergraduate students from rural communities and small towns are underrepresented in CU Boulder.


Comparison of Dynamic and Linear Programming using Weighted Job Scheduling Problem


Compared Dynamic Programming and Linear Programming in solving the Weighted Job scheduling problem with increasing jobs and increasing hardness of the problem.


Study of user activity on Question-Answering Platform : Stack Exchange


Leveraged questioning-answering activities of users on Stack Exchange platform to study the latent community structure between various Q&A websites using Stochastic Block Modeling.


Movie Recommendation System : Kaggle Dataset


Using user demographics and the movies they have watched and rated, built a model to recommend movies to the users which they have not watched yet but are very likely to rate highly.

Contact


upasanad <at> seas <dot> upenn <dot> edu


Dept. of Computer and Information Science

University of Pennsylvania

Philadelphia, PA 19104


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