• Developed a full-stack AI application utilizing Python, OpenCV, and advanced Computer Vision techniques to detect, process, and map handwritten exam questions from images.• Designed and implemented a user interface allowing users to upload images and retrieve processed results, integrating Image Processing workflows via JavaScript on the frontend and Node.js for backend communication.• Engineered a backend architecture using Node.js and Python Flask, enabling real-time image processing, data mapping, and handling through API requests, utilizing FormData and Axios for seamless integration.• Managed and deployed backend services using Docker Compose, orchestrating Python Flask, Node.js Express, and MySQL servers for efficient scaling and seamless interaction.• Implemented a MySQL database system to store, map, and efficiently manage large datasets, ensuring smooth interaction between the database and application.

• Conducted hardware diagnostics and performance testing, identifying system bottlenecks and optimizing both CPU and GPU architectures for improved functionality.• Collaborated with the engineering team to integrate hardware components, ensuring seamless compatibility and performance across various subsystems.• Engaged in system optimization, focusing on hardware-level performance tuning and ensuring reliable and efficient operation of embedded systems.• Gained experience in hardware-software integration, troubleshooting, and maintaining high system performance standards.