Guilherme Janssens Akrouch

The main goal of this ongoing project is to provide a complete virtual enterprise-focused travel agency where clients can self-manage their staff trips and apply specific travel policies to particular users or sectors. The application also offers a full expense service, allowing users to upload receipts and register expenses made during trips.

I developed the mobile app, which currently possesses multiple finished modules but has not been released yet. Among all the functionalities, it seems relevant to highlight the push notifications for both Android and iOS and peripherals integrations, like the camera for reading receipts or taking pictures. The app also provides functionality to determine whether the device is still connected to the internet, notifying the user not to proceed with any trip creation process that depends on third-party APIs (car rentals, airline companies, or hotel providers).

Utilizing Python, I developed an OCR for reading Brazilian-type receipts. With Google's OCR, I can identify the amount spent and the company's unique ID and address, contributing to our expense module.

An app provides manageable and operational data from claw machines to a specific company with 300+ devices.

The system consisted of consuming data derived by microcontrollers installed in the machines provided by the company. The API would communicate with the front-end mobile and web applications and provide real-time data about the statuses of the machines and other data like prizes sold and plays.

Specifically, my job was to implement the mobile application (iOS and Android) with Flutter and build the AWS Lambda function in Python that received the telemetry logs directly from the microchips, adding them to the database (MongoDB) to be utilized by the RestAPI and provide data to the front-ends.

This project aimed to provide complete delivery independence for restaurants, giving the clients a web portal to manage the operation and a cross-platform Flutter mobile application for the users to order food.

I contributed to an iOS and Android cross-platform Flutter-based mobile app by providing all necessary functionalities for users to order the food, properly integrating it with our API developed by another team in the company. Also, I deployed the mobile applications in Google Play Console and App Store Connect. In addition to that, I assisted in the system's architecture, raising requirements, and modeling the database.

This project consisted of rebuilding possible trajectories that stranded animals might have traveled, utilizing the Lagrangian model of particle transportation principles.

The algorithm started with the coordinates the stranded animal was found and mathematically backtracked its location to an input number of days utilizing open-source data of Brazil's coast ocean currents.

The database was built from open-source data created by the project OSCAR from NASA, and the algorithm implemented the Lagrangian model reverse.

This project was part of my final thesis in 2020, so I was the only contributor to the project covering all aspects of it.

Canary Speech is a Flutter cross-platform mobile application with the purpose of facilitating mental illness diagnosis in corporations and companies.

The app consists of custom assessments built by these corporations to be taken by their employees. The app builds each assessment based on its components, varying from voice recording to multi-choice questions.

My involvement was mostly in the app's UI with the proper state management and its integration with the client's back-end application.

Tea is a Flutter cross-platform social-media-like application for women to help each other navigate the complexity of today's relationships. On Tea, users can share real-life experiences with each other and experiences from dating apps like Tinder.

I was responsible for developing the whole application from scratch with all the necessary features: real-time chat, push notifications, dynamic links, etc.

As a consultant, I worked with a small team of developers on an early-stage project. The goal was to analyze the current code and suggest improvements in code quality, code architecture, and organization in order to achieve a highly maintainable, scalable, and readable codebase.