Advancing Privacy in Federated Learning

My research aims to improve data privacy in AI by developing better methods for privacy-preserving machine learning. Federated Learning and Differential Privacy allow AI models to be trained without sharing sensitive data, but stronger privacy often reduces model performance. This project works to close that gap by creating open-source tools that help developers build AI systems that are both private and effective, supporting responsible and transparent AI innovation.