ABOUT ME

WA

I'm a computer scientist who graduated from the Federal University of Alfenas (Unifal-MG) in 2022.

I currently work as a junior fullstack developer, where I've been developing my skills on the front-end using React/Next.js and Flutter, and on the back-end with PHP and SQL Server.

I'm also familiar with data science and machine learning. In December 2023, I had the opportunity of publishing my article entitled "Study and Analysis of Deep Learning Techniques for Solving Financial Problems" in the journal 'Learning and Nonlinear Models'.

In addition to development, I am also passionate about the GNU/Linux ecosystem, which I use daily as my primary system for both development and leisure.

EDUCATION

PROFESSIONAL EXPERIENCE

Junior Fullstack Developer

Exportadora de Café Guaxupé Ltda.

Jul 2023-Present
  • Development of web systems using PHP + SQL Server in the backend and React/Next.js in the frontend.
  • Integration with REST APIs for automating data retrieval and submission using PHP + curl.
  • Retrieval and treatment of geographic data and open data using Python.
  • Development of mobile apps using Flutter.
  • Development of integrations and customizations for the TOTVS Protheus ERP system.

Front-end Developer

TriBit Jr. - Unifal-MG Junior Enterprise

May 2017-Apr 2019

Front-end development using HTML, CSS, Bootstrap, Ionic and Firebase.

PUBLICATIONS

COURSES AND CERTIFICATIONS

SKILLS

Programming Languages

Type­script
PHP
Python
Dart
Ja­va
C
Lu­a
Bash

Frameworks, Technologies, etc.

Next­.Js
Re­act
Tail­wind CSS
Flut­ter
SQL Serv­er
My­SQL
HTML 5
CSS 3
Git
Arch Lin­ux
Adobe Pho­to­shop
Ink­scape

Machine Learning

Ke­ras
Num­py
Pan­das
sci­kit-learn
Mat­plot­lib
Hy­per­opt

Languages

Brazil­ian Por­tuguese
Eng­lish

PROJECTS

Environmental Compliance Platform Frontend, made with Next.js 14, MUI, and Tailwind CSS. Internationalization made with next-intl.

Command-line utility for performing mass edits on wikis using the MediaWiki API. Made with Python, inspired by AutoWikiBrowser.

Code used for exploring machine learning and deep learning techniques using data from the machine learning competition "Jane Street Market Prediction".

Next.js 14 Starter SSG project with client-side locale detection and internationalization with next-intl.

A responsive web dashboard with sidemenu and routing, made with Flutter Web.

Routes visualization with Google Maps and existing coordinates.

PHP authentication API using JWT and SQL Server.

Terminal-based chess game made with Java.

Program written in C that counts stars in astronomical images using parallelism with MPI.