Rodrigo C. Garcia
Computer Science Student
Aspiring Software Engineer
Important Links:
Commodities Price Prediction (Python/N8N)
Prediction of commodities prices using Machine Learing and N8N flow for the most recent data
Binary Tree Visualizer (Java)
Interative app to create and visualize the different types of binary trees
Sonic Recreation (C)
Recreation of the game Sonic the Headhog using Raylib. Everything made from scratch in C!
Background and Tech Stack
Born in Brazil, I have always been fascinated with technology. Ever since a young age I was at the family computer messing about, or downloading games from sketchy websites. At around 14 years old I decided that I wanted to learn programming and started learning Python, which I did mostly for fun. When I finished high school I knew I wanted to work with tecnology but I couldn't go to college because of my family's financial situation and the pandemic, so I had to work for 2 years while studying for college entrace exams before starting my Computer Science degree. I moved from São Paulo to the small city of São João da Boa Vista to pursue my dream of working in IT. It has been an amazing journey so far and I learned so much in university and I am eager to put what I learned to practice. Here is a look at the tools and technologies I work with:
Python & Data Analysis
Development of complete solutions for exploratory data analysis and structuring using libraries like Pandas, Scikit-learn, and Plotly Dash.
Machine Learning
Practical and academic background in machine learning algorithms, including reinforcement learning implementations using environments like Gymnasium.
Computer Vision & Image Processing
Experience handling image processing and visual representations utilizing OpenCV, including algorithms like CLAHE for image segmentation.
Java & Android Development
Building interactive applications and structured data displays using Java (Swing, JavaFX) and Android XML (RecyclerView, GridLayoutManager).
C & Algorithm Design
Implementation of complex game logic, collision detection with Raylib, and heuristic-based solvers (such as IDA* with Manhattan Distance).
LaTeX & Technical Documentation
Advanced proficiency in structuring academic reports, managing bibliographies, and typesetting complex mathematical equations.