Evan Dong is a PhD student in Computer Science at Cornell Tech advised by Nikhil Garg and Angelina Wang. Their research combines conceptual interests in identity and social construction with optimization and machine learning methods to interrogate the processes that translate algorithmic model outputs into real-world classifications and decisions. Their past work has touched on structural disparities in voter demographic data, formal limitations to school admission prediction systems, and ontological tensions in bias audit methodology. As a DLI Doctoral Fellow, Evan aims to build a rigorous foundation to make normative privacy and equity claims about how model outputs should be interpreted.