I'm a Fullstack Developer focused on learningand building real-world web apps.
I combine a strong foundation in fullstack development with a growing passion for building accessible, performant web apps. I'm currently focused on learning modern web technologies, design systems, and crafting real-world digital experiences.
Università degli Studi della Campania Luigi Vanvitelli
Erasmus for the final year of university and final degree project completed in Naples. The most relevant subjects are: Distributed System, Knowledge Engineering and Artificial Intelligence, Advanced Software Engineering and Machine Learning
Facultat d'Informàtica de Barcelona - Universitat Politècnica de Catalunya
My experience in the Bachelor's Degree in Computer Engineering has provided me with the skills, abilities, and knowledge necessary to work in the field of computer engineering. Focusing my career on the Software Engineering specialty, I am highly qualified in programming, analyzing, and integrating systems and applications. This solid technical foundation prepares me for the management of IT projects and departments, addressing a wide variety of work areas in software and management.
AgileCC++CSSData Structure and AlgorithmsDjangoHTMLJavaScriptJSONLinuxOOPOpenGLParallel ProgrammingPostgreSQLPythonSCRUMSoftware ArchitectureSQLVue.js
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Featured Work
A selection of projects that showcase my expertise in building modern web applications with focus on user experience and performance.
Trackr - Video Analysis Platform with Person Detection
This project is part of a Bachelor's Thesis and consists of a platform developed with Django that allows users to upload videos via a web interface and receive them back with bounding boxes highlighting the detected people in each frame. Its modular architecture allows for future expansions to other detection types. It includes AWS S3 cloud storage integration, and is divided into two Django apps: one for backend logic and another for the web interface.
Trackr API - Object Detection Microservice with FastAPI
Microservice built with FastAPI that processes videos hosted on Amazon S3 using own object detection models developed from the infrastrucutre of YOLO. The system generates an annotated version of the video with detected objects, which is reuploaded to S3. The API response includes both the original and processed video URLs, along with metadata about the detections (classes, counts, timestamps, etc.). It is part of a larger video analysis system focused on person detection.
Kbin Interface - Collaborative Frontend Inspired by Kbin
This frontend was developed as part of a team project using Vue. Inspired by the Kbin platform, it connects to a Django-based backend. It was deployed on Heroku.
Kbin Fullstack - Complete Web Project Inspired by Kbin
Full web project (frontend + backend) inspired by the Kbin platform. Developed by team bravo13, it uses Django for the backend and web technologies like HTML, CSS, and JavaScript for the frontend. The application was deployed on Heroku and represents an integrated social or content aggregator solution.
Airmon - Backend for Monitoring in an Academic Environment
This backend was developed for the Airmon project, part of the PES course (QP23-24). It uses Python 3.11.5 and is intended to run on Linux environments (Ubuntu 22.04). The environment is managed using venv and pip. Although it is an academic project, its structure and setup make it easily extendable to production environments.