I single-handedly designed and implemented various full-stack platforms using mainly VueJS / Nuxt, NodeJS, Google Cloud / Firebase:- Invest-t (https://invest-t.it) a lending crowdfunding for real estate investments integrated with the payment system Lemonway using JSON APIs running on the serverless service 'Google Cloud Functions' (NodeJS).- FlatFox (https://flatfoxitalia.it/) a software providing ROI predictions about investment opportunities, running on Firebase with its NoSQL DB and VueJS on the frontend.- PuntoZero CRM (https://gestionalepuntozero.app/) a management software used internally, also designed and developed full-stack, using VueJS and Firebase.

We used a micro-services architecture. The applications/services were written in Java and managed on Google Cloud using Docker and Kubernetes.
I also built the whole frontend service with a subset version of Java using GWT, a tool compiling Java code to JavaScript. I integrated numerous tools for user analytics (e.g. Google Analytics, Hotjar, Mixpanel), communication (Intercom), and other functionalities (Highcharts to draw charts and graphs).
I developed a custom integration for the Stripe payment system (and a 3rd party tax library) while designing and managing the whole payment workflow, including internal notifications and APIs.
I implemented the user permissions system and the user session flow.
I developed an admin dashboard to internally manage our users and their data.

The first work (Weaving Communities of Practice project), with an Agile methodology, consistsof building a web application for access and consulting informations stored as RDF triplesand hierarchical structured by the means of an RDFS ontology. The application is developedin PHP5 (using MVC), JQuery and AJAX. The queries are executed using the SPARQLlanguage.The second work (MiGen: Intelligent Support for Mathematics Generalisation project) consists ofbuilding a test application structure to discover the limitations of the system in terms of response time and overloading. The tools involved are Java and JavaScript based.

The work concerned the development of an Android mobile application that allowsthe user to execute geo-localized tags and queries, using the natural language.Subsequently I investigated the state of the art to implement a Java backend onGoogle App Engine, capable of generating a ranking of the tags on the basis ofspace-time context and semantic similarity. To do this I implemented two mainalgorithms, one to compute the similarity between words and the other to computethe similarity between phrases, previously structured according to an object modelcreated to represent the English grammar.

During the university period I worked as freelance developer, building numerous applications(management and web based) in various programming languages (mostly Java, Python,PHP and JavaScript), often interfacing with a database.