Romain Matheos

Client Portal : Developed an internal web platform for client project management, featuring a comprehensive dashboard to monitor project status and deliverables. The platform includes functionalities for document signing and payment processing. Implemented a new ticketing section, allowing clients to submit requests.

CBA : Designed and developed a custom platform from scratch for a client to streamline event organization with their community. The platform includes features for managing attendees, events, and email templates. Users can create events, generate targeted guest lists, and automatically send email invitations using customizable templates.

Technical environment : FLUTTER - AIRTABLE - FIREBASE - BITBUCKET - ASANA

- Object-Oriented Architecture

- CRUD Integration with Airtable API

- Configurable and Reusable Widgets

- Authentication System

- State Management using Riverpod and Provider

- Deployment on Firebase

Cocoto : Development of new interfaces for flight engineers, enabling control and monitoring of flight tests. Implementation of real-time curve display, sliding canvas system to simulate infinity.

Print2Ipad : Development of an application for capturing screenshots of all screens on the engineer station during flight test. Possibility to annotating capture directly with the Ipad. Storage of captures in indexedDB and cache the app with service workers to allow offline mode (outside of plane).

FTES Banner : Creation of a banner for the new flight test engineers station. Style reproduction of mechanical buttons used to launch commands via SNMP and SOAP protocol (Screenshot, Recording, Chrono... ).

WebFTI : WebSocket server for reading the IENA stream containing all flight test data.

Technical Environment : APACHE SERVER - JAVASCRIPT - PHP - HTML - CSS - JQUERY - LINUX - GIT

- Object Oriented architecture

- AGILE methodology organization

- Virtual machine Linux Cent OS

- Configurable and reusable widget and blocks

- Page defined by configuration files (JSON & XML file)

- Real time update ( < 200ms )

Application for labelling data with the aim of creating customizable data models to train deep learning algorithms. I developed a system to allow object detection for image labelling. Next I add a pre-labeling feature using OpenCV, Ultralitycs and YoloV8.

Technical environment : ANGULAR - NEST - PYHTON - GRAPHQL - MONGODB - DOCKER - JASMINE - KARMA - JEST - GITLAB - LINUX

- Creating of reusable components

- Creating services, modules, and controllers

- Creating models and routes

- Creating JSON BDD schema

- Integration of YoloV8 algorithm

- Bounding box creation using canvas