Gina Maninno

• University of Notre Dame
• Tech Ethics Graduate Fellow (2026-2027)

Gina Mannino is a Ph.D. candidate in applied and computational mathematics and statistics at the University of Notre Dame, where she is advised by Dr. Fang Liu. Her dissertation research focuses on balancing the statistical utility of synthetic data with differential privacy. Specifically, her work addresses the challenge of releasing useful information about datasets while safeguarding individuals through heterogeneous differential privacy methods and large language models for synthetic tabular data generation. By developing approaches that preserve data utility without compromising confidentiality guarantees, her research advances responsible data sharing practices that enable transparency while protecting individuals.

Before pursuing her Ph.D., Mannino obtained a bachelor of science in mathematics and chemistry at Franciscan University of Steubenville. She spent two years working as a Senior Research Associate at the Building Inclusive Growth (BIG) Lab in the Economics Department at the University of Notre Dame, where she focused on data analysis and project management in the areas of labor and developmental economics.