Computer Engineer with hands-on experience designing and developing scalable web and mobile systems. Strong interest in AI-driven solutions, data-oriented systems, and performance optimization, delivering structured and production-ready outcomes in agile environments.
Full-stack developer who built cross-platform mobile apps (iOS/Android) with React Native, developed real-time chat and notifications with Socket.IO, implemented secure REST APIs with Node.js and JWT, and contributed to AI-powered platforms using deep learning models, dashboards, and MongoDB for analytics and reporting.
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As part of our graduation project, I contributed to developing an AI-powered road defect detection system using Python and YOLOv8. I worked on the computer vision pipeline, including dataset preparation, image processing, model training, and evaluation for detecting road defects such as cracks and potholes.
I also developed the Flask backend and REST APIs, integrating the AI model with the web interface and database layer. This project strengthened my skills in deep learning, computer vision, backend development, and deploying AI-based solutions.
As a core developer, I contributed to building a cross-platform social and information platform for vehicle and motorcycle enthusiasts. I worked across the full-stack, developing the mobile application with React Native and Expo, backend services with Node.js and FastAPI, and data management with MongoDB.
I implemented JWT-authenticated REST APIs, real-time chat and notifications using Socket.IO, and contributed to OpenAI GPT-4o integration for AI-powered vehicle information and content classification. I was also involved in performance optimization, feature development, and deployment, strengthening my full-stack development, problem-solving, and teamwork skills.
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