Christlei Daniel Aguila

I am a Computer Science student with a strong foundation in programming and software development, backed by hands-on experience in a wide range of technologies. Over the course of my studies, I have gained proficiency in multiple programming languages and frameworks, applying them to various academic and personal projects. My background demonstrates not only technical skills but also adaptability, problem-solving abilities, and a genuine passion for continuous learning.

Throughout my academic journey, I have developed several projects that showcase both my technical knowledge and creativity. One of my earliest projects was a web development exercise using pure HTML, CSS, and JavaScript, where I was able to strengthen my understanding of front-end design, user interaction, and responsive layouts. This project helped me build a solid foundation in web technologies and fostered a deeper appreciation for the importance of usability and accessibility in software development.

Another project I worked on was a crossword puzzle game, developed as a native Android application using Kotlin and Jetpack Compose. This experience introduced me to the world of mobile development, where I learned about UI design, state management, and handling user interactions in an engaging way. It also enhanced my skills in structuring code for maintainability and scalability, which are crucial in mobile and enterprise applications.

Among all the projects I have completed, my most significant and meaningful work is a nutritional application that I consider my highlight as a developer. This project combined multiple technologies and pushed me to integrate software engineering with artificial intelligence. The app was developed using TypeScript/JavaScript, React Native, and Expo Go, ensuring cross-platform compatibility and a smooth user experience. On the backend, I utilized Python FastAPI for API development and Supabase as a backend-as-a-service (BaaS), which streamlined database management and authentication.

What sets this project apart is the integration of an AI model that I developed to detect and classify three types of fruits. Using YOLOv8 as the base model, I trained the model on a custom dataset that was preprocessed and normalized with Roboflow, and the training itself was carried out on Google Colab. This experience taught me valuable lessons in data handling, machine learning model training, and deploying AI-powered features into real-world applications.

Overall, I consider myself highly adaptable to different programming languages and development environments. My strong foundation in computer science allows me to quickly grasp new technologies, while my collaborative spirit makes me enjoyable to work with. I am passionate about learning from peers and mentors, and I thrive in environments where I can continuously improve my skills while contributing meaningfully to a team’s goals.