I am a Computer Science Ph.D. student at the University of Houston focusing on Responsible and Ethical AI, with a primary emphasis on dataset evaluation. My research examines how datasets are constructed, documented, and maintained, and how their statistical and structural properties influence fairness, privacy risk, and reliability in AI systems.

My work involves designing and building frameworks to evaluate AI datasets and the codebases used to develop models. I apply these frameworks to assess dataset quality, dataset fairness, and privacy risk, with a particular focus on medical tabular data. In parallel, I evaluate repositories for responsible development practices such as reproducibility, documentation quality, privacy safeguards, and basic ethical and compliance signals. By defining clear metrics and auditing criteria and using them to surface bias and risk, I support more careful and accountable AI development.