Hey, I'm Gabriele Firriolo
Full-Stack Developer & AI Enthusiast
I build scalable applications and move ideas from prototypes to production. Based in Italy, with TypeScript, Next.js, Python, and Machine learning, I craft fast, accessible, and data-driven products that feel delightful to use.
My Journey
Work Experience
Full Stack Developer
SuperUrbanity
Full-time hybrid position in Bergamo, Lombardia. Working with modern web technologies and creating AI-driven solutions.
AI Developer
Freelance
Machine Learning project for basketball game statistics (box score) analysis using computer vision. Leveraging YOLO to detect players and actions from videos, automating statistical data collection.
Full Stack Developer
CyberizeSolutions Italia
Freelance remote position in Bergamo. Developed comprehensive web applications using modern JavaScript frameworks and technologies.
Software Developer Internship
Lutech (ex DISC)
PCTO activity during school at I.T.I.S PALEOCAPA. Team organization for software development, risk and cost analysis, GitHub collaboration, and project security analysis with SonarCloud.
Education
Bachelor of Science - Computer Science
Università degli Studi di Milano
Thesis: "Semantic reasoning with structural features in 2D robot grid-maps". Focused on algorithms, AI, machine learning, and software engineering.
Diploma Computer Science
I.T.I.S P. Paleocapa
Diploma in Computer Science. Deepening in full-stack development, algorithms, security (OWASP), and object-oriented programming.
Featured Projects
Basketball Analytics AI
Computer Vision for Game Statistics
Basketball Analytics AI
Machine Learning project for basketball game statistics (box score) analysis using computer vision. Leveraging YOLO to detect players and actions from videos, automating statistical data collection in real-time.
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Semantic Reasoning with structural features
Research project to enable robots to understand their indoor environment by identifying high-level structural features from the map.
Semantic Reasoning with structural features
This project proposes a system to enable robots to understand their indoor environment by identifying high-level structural features such as walls, rooms, and directions of movement directly from the map. The system uses SLAM and ROSE2 to extract these features from a 2D map built from indoor environments. The results are used to train CNNs to recognize these features automatically.
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Web Scraping System
Web Scraping System to automate data collection for a certification company
Web Scraping System
Scalable Web Scraping System to automate data collection for a certification company. Analyzed and processed extracted data to optimize business processes supporting human operators in generating leads.
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AFSE Marvel
AFSE Marvel is a web application that allows users to create and manage their own Marvel Comics collection.
AFSE Marvel
AFSE Marvel is a web application that allows users to create and manage their own Marvel Comics collection. The application is built using React and Node.js, and it provides a user-friendly interface for users to add, remove, search and exchange their comics.
Read MoreLet's Connect
I'm always open to new opportunities and collaborations.
Feel free to reach out if you'd like to connect!