I am an AI researcher with a Ph.D. in Computing & Information Science from the University of Nebraska Omaha. My research investigates how neural networks encode semantic structure that remains stable under perturbation. I study how these invariant representations emerge, how they can be systematically learned or identified, and how they can be operationalized for robustness-critical applications.

My work has focused on robust watermarking and model provenance as downstream applications and as quantitative probes of representational stability. On the vision side, I have developed frameworks for semantically grounded invariant feature learning and camera-robust zero-watermarking. On the language side, I have designed black-box LLM watermarking systems, and investigated the geometric structure of invariant subspaces in pretrained LLMs for model attribution.

Outside of research, I like playing video games and badminton. I also occasionally draw and make YouTube videos when I feel inspired. I love dogs.