Professor of Applied and Computational Mathematics and Statistics
Department: Applied and Computational Mathematics and Statistics
Research interests: Data privacy, differential privacy, statistical machine learning
One of Fang Liu's major research interests is data privacy and differential privacy. Differential privacy provides a strong mathematical guarantee for individual privacy when releasing information and data. Liu's work focuses on generating differentially private synthetic data, differentially private optimization problems, and understanding of the statistical and inferential properties of the differentially private analyses, among other areas. Liu is also interested in understanding fairness and bias of machine learning algorithms and algorithmic decision-making.