Browser-based eye-tracking application built with a React frontend and Django backend, designed to help sports coaches analyze how athletes visually process game footage. The platform combined AI-driven gaze detection with video playback, allowing it to determine what specific elements players were looking at during precise moments in the footage. Coaches could define high-priority areas of interest (such as key players, ball movement zones, or tactical regions on the field) and then evaluate athletes based on how much visual attention they dedicated to feedback on an athlete's focus patterns over time. My contributions focused primarily on the frontend, where I feedback on an athlete’s focus patterns over time. My contributions focused primarily on the frontend, where I implemented features to support video playback overlays, gaze visualizations, and data-driven dashboards. I also took responsibility for unit testing the frontend, ensuring that core UI components and data visualizations functioned reliably and integrated correctly with backend analytics. Through this project, I gained hands-on experience in AI-powered sports analytics, frontend development, and quality assurance, while helping deliver a tool that bridges cutting-edge technology with real-world athletic performance analysis.
Mobile application inspired by the classic Snake game, where players control their snake by physically walking around in the real world using their phone. Built with React Native (Expo) for Android/iOS, with a TypeScript and Express backend to track player locations, manage points, and synchronize game state via WebSockets. Integrated Google OAuth2 for secure player authentication and session management. My primary responsibilities included implementing the mobile frontend and Google OAuth integration, as well as creating and implementing game logic. Collaborated closely with a three-person team, participating in weekly meetings for discussion and peer programming.