PhD Student at University of Colorado Boulder, United States.
Upasana Dutta is a PhD candidate in Computer and Information Science at the University of Pennsylvania, specializing in network analysis, machine learning, and social media behavior. With an impressive academic record and a diverse research portfolio, she has significantly contributed to the study of partisanship in media, epistemic bias in research, and online user behavior analysis.
Publication Profile
Google Scholar
Education
Upasana Dutta is currently pursuing a PhD in Computer and Information Science at the University of Pennsylvania, maintaining a GPA of 3.88/4.0. Her academic journey includes a Master of Science in Computer Science from the University of Colorado Boulder, where she achieved a perfect 4.0 GPA. She completed her undergraduate studies with a B.Tech in Computer Science and Engineering from Heritage Institute of Technology, India, graduating with a GPA of 9.36/10. Throughout her academic career, Upasana has demonstrated strong proficiency in machine learning, natural language processing, and network analysis, receiving high accolades and recognition for her research contributions. Her solid educational foundation has provided her with the skills to tackle complex problems at the intersection of computer science and social sciences.
Experience
Upasana Dutta has gained extensive research experience in both academic and applied settings. As a Research Assistant at the Clauset Lab at the University of Colorado Boulder, she analyzed network statistics in various real-world networks, including social, biological, and technological systems. She also conducted research on user behavior in response to the Russian Internet Research Agency’s actions during the US 2016 elections. Upasana has worked with leading experts like Duncan Watts and Aaron Clauset, co-authoring several impactful publications in the fields of machine learning, media bias, and network analysis. Additionally, she has served as a Teaching Assistant for courses in natural language processing and given tutorials on networks at the Summer Institute of Computational Social Science. Her work continues to influence research on social media behavior and its broader societal impact.
Awards and Honors
Upasana Dutta has received several prestigious awards for her research excellence. She was honored with the Abel Lukens Stout Fellowship at the University of Pennsylvania in 2022 and the Bell Foundation Outstanding Research Award at the University of Colorado Boulder the same year. Upasana’s work was also recognized with the CS Annual Research Expo Award at CU Boulder in both 2021 and 2022. She was a finalist for the NCWIT Collegiate Award in 2021 and earned the CS Publication Recognition Award for her publication on social media behavior. Her academic achievements have been celebrated throughout her educational journey, showcasing her exceptional contributions to computer science and social media research. These honors reflect her ongoing dedication to advancing research and her potential to lead in her field.
Research Focus
Upasana Dutta’s research focuses on the intersection of computer science and social science, specifically in the areas of social media behavior, media bias, and network analysis. Her work explores how machine learning can be used to analyze large-scale datasets, such as TV news episodes and online platforms, to detect partisanship and bias. She has also investigated the impact of ideological exposure on user behavior in digital environments, particularly on platforms like Twitter and YouTube. Additionally, Upasana is exploring epistemic bias in research through meta-analytic studies and applying machine learning to understand researcher biases in scientific publishing. Her interdisciplinary approach combines technical skills in machine learning and network analysis with a deep understanding of social dynamics, aiming to drive meaningful insights in media consumption and behavior.
Conclusion
Upasana Dutta’s research has made a remarkable contribution to the fields of computer science, social networks, and media studies. With her exceptional technical skills, notable publications, and recognition through prestigious awards, she is a strong contender for the Best Researcher Award.
Publication Top Notes