Hello, I am Caio Canalli.

Full Stack Developer.

About me

Computer Science student at IFSP with a strong focus on evolving into a Full Stack Developer. Building upon a solid foundation in algorithmic problem-solving and robust technologies like Java and C, my primary goal is creating efficient, high-performance applications.

With a background that spans CNPq scientific research fellowships and formal training in Mechatronics, I bring a highly analytical, data-driven perspective to software architecture. Beyond core programming, I leverage tools like n8n for process automation, integrate complex APIs, and apply NLP concepts to build smarter applications.

Backed by an international English certification (Michigan Language Assessment), I am fully equipped to collaborate within global, agile teams and eager to contribute to scalable, innovative software solutions as I transition into the industry.

Undergraduate
Computer Science, IFSP
Research
Scientific research fellowships
Technical training
Mechatronics

Skills

Languages
  • Python
  • Java
  • C
  • Dart
Development and automation
  • Web Developing
  • Flutter
  • API Integration
  • n8n
Data and AI
  • MySQL
  • PostgreSQL
  • SQLite
  • Power BI
  • NLP Concepts
Tools and practices
  • Docker
  • Git / GitHub
  • Claude Code
  • Agile Methodologies
  • Algorithmic Problem-Solving

Journey

  1. Grant Holder

    FACTO, Fundação de Apoio ao Desenvolvimento da Ciência e Tecnologia

    to

    I work as a developer in a software-house-style development cycle: gathering requirements and use cases, building tracking tools and linking business requirements to technical solutions.

  2. Undergraduate Research Fellow

    COSAIC Project, FUNARBE / INOVA IFSP

    to

    In the NLP role, I worked with predictive models and recommender systems for digital learning resources, plus AI automation workflows in n8n and reports in LaTeX.

  3. Apprentice

    Scalla Cerâmica Artística

    to

    I supported industrial production and maintenance: assembly, calibration and testing of electromechanical components, preventive maintenance, and inspection and quality-control routines.

Projects

  • AI Commodity Forecasting

    Intelligent data ecosystem for forecasting and analyzing agricultural commodity prices using Machine Learning (XGBoost). Built with a Python ETL pipeline, continuous automation via n8n, Supabase, and an interactive Power BI dashboard.

    • Python
    • n8n
    • Power BI
    • Machine Learning

    CONICT 2026 paper (PDF, in Portuguese) (opens in a new tab)

  • Supply Chain Platform

    An integrated platform designed to monitor logistical bottlenecks, featuring automated supplier notifications powered by LLMs for vendors with high defect rates, alongside interactive data dashboards.

    • MySQL
    • n8n
    • Groq LLM
    • Power BI

    Live demo (opens in a new tab)

  • LibrasRec

    A real-time Brazilian Sign Language (Libras) to alphabet converter and detector that leverages computer vision to process inputs directly through the computer's webcam.

    • Python
    • OpenCV

    Code on GitHub (opens in a new tab)

  • High-Performance Trie Search

    A Java Swing application implementing an R-way Trie data structure for ultra-fast text indexing. It accurately maps and returns the exact line and column positions of words or emojis within documents.

    • Java

    Code on GitHub (opens in a new tab)

  • Sorts Simulator

    An interactive algorithm simulator designed to visualize and analyze the mechanics and performance of various sorting methods.

    • Java

    Code on GitHub (opens in a new tab)

  • GourmetLab

    A smart mobile application acting as a gastronomic laboratory to manage pantries and fetch custom recipes. Features offline access via SQLite and an optimized batch translation engine for external API data.

    • Dart
    • Flutter
    • SQLite
    • C

    Code on GitHub (opens in a new tab)