Sina-Marie Mayer

Master of Public Informatics, Class of 2026

M.Sc. Social and Economic Data Science & Master of Public Informatics

From Social Science to Data Science

Sina’s journey into Public Informatics began with a strong interest in data-driven decision making in government and policy. While pursuing a Politics & Public Administration degree in Germany, she focused heavily on quantitative research and statistical methods. During this time, she noticed a recurring challenge: policymakers often had access to large amounts of data but lacked the capacity to create meaningful action. This realization sparked her interest in data science and AI for public impact, ultimately leading her to the MPI program at Rutgers. As a DAAD-ISAP Scholar, she is currently pursuing a double degree between the University of Konstanz and the Bloustein School, combining advanced analytics with real-world policy applications.

Academic Experience at Rutgers

The MPI program pushed Sina to expand beyond quantitative foundations into applied technical work. Courses such as Machine Learning for Public Informatics and Advanced Quantitative Methods helped her think not only about building predictive models, but also how to use it responsibly in public sectors. Her highlight has been the Public Informatics Studio course, where students work with real-world clients throughout the semester. The course applying analytical tools to practical problems while developing essential skills in team collaboration and communicating insights to stakeholders.

Research and Hands-on Projects

Her research focuses on AI, public perception, and governance. In a directed research project, she analyzes large-scale Reddit data using natural language processing and topic modeling to examine how fear and stress appear in public discourse around artificial intelligence. She also contributed to a project developing a hybrid NLP pipeline to detect early signs of dementia from speech data, combining semantic network analysis with transformer-based language embeddings while prioritizing explainability for clinical interpretation.

Future Vision

After completing the MPI program, she plans to finish her Master’s in Social and Economic Data Science in Germany, further strengthening her methodological and technical expertise. In the long term, she hopes to work at the intersection of AI, data science, and public policy to support evidence-based policymaking, improve public services, and better understand how society responds to emerging technologies.