Bloomington, Indiana, United States
I’m a Computer Science student with experience building full-stack systems. Recently, I helped rewrite a legacy application for an IU research lab and built a news-style blog platform with secure authentication, role-based access control, and Redis-backed caching. I'm especially interested in backend development, distributed systems, and low-level computing. This includes operating systems, computer architecture, and embedded development. I'd like to work in these areas not only for fun but also due to my interest in defense and national security. What motivates me is solving challenging and meaningful problems. Whether that’s designing complex infrastructure, building tools to support researchers, or improving site accessibility. It's rewarding knowing that my work has impact at the end of the day.
Modulated Signal Tracking in Dynamic Environments - Contributed to research on visible light communication (VLC) systems for autonomous platforms. - Designed real-time algorithms for LED detection, clustering, and motion tracking using event-based vision sensors. - Investigated clustering strategies and noise filtering techniques to robustly identify LED events under high noise conditions. - Implemented Kalman Filter–based tracking models to predict nonlinear LED motion, improving communication stability at high vehicle speeds.
- Rewrote endpoints and implemented robust security measures (filename sanitization, RCE prevention, OAuth2.0 OIDC authentication), resulting in enhanced application security and maintainability. - Improved real-time performance by designing an asynchronous architecture for long-running processes (e.g. background tasks, multithreading, shortpolling), improving user experience. - Designed a modernized and responsive UI with React and IU’s component library, improving user experience. - Streamlined development and deployment workflows through containerization, script automation, and CI/CD pipelines.
Automated PDF Redaction Pipeline - Built a document-processing pipeline to automatically detect and redact sensitive information in PDFs. - Supported both text-based and scanned PDFs using regex-based PII detection, token-matching, and Object Character Recognition (OCR). - Generated redacted PDFs with bounding-box masking, along with detection logs and audit reports. - Collaborated with a team to design an end-to-end workflow that reduced manual review time and improved data-privacy compliance