Spencer - Giddens
Department: Applied and Computational Mathematics and Statistics
Advisor: Fang Liu
Spencer Giddens received his B.S. in Applied and Computational Mathematics, and his M.S. in Mathematics, both from Brigham Young University. He is currently working on his Ph.D. at Notre Dame in Applied and Computational Mathematics and Statistics. His focus is on differential privacy, a framework for providing mathematical guarantees of privacy for individuals whose sensitive data is used to produce summary statistics and develop statistical/machine learning models. His recent work on this subject includes developing DPpack, a software package for the R coding language that focuses on providing easily accessible implementations of differential privacy for common statistical procedures. Going forward, he hopes to develop novel methods to apply differential privacy to Individualized Treatment Rules, a class of algorithms that use clinical/medical data to optimally assign treatments to patients with the goal of maximizing the expected treatment benefit.