Gustavo Casadei Bellanda

I'm

Production Engineer & Artificial Intelligence Developer

  • Birthday: May 12, 2000
  • Phone: +55 (16) 9718-4720
  • City: Catalão, Brazil
  • Languages Portuguese native & advanced english

About Me

I am a Production Engineer and Artificial Intelligence Developer focused on innovation and continuous learning. My career is marked by a strong commitment to operational efficiency and technological advancements, aiming to integrate practical solutions and emerging technologies.

Professional Philosophy

Combining technical expertise and strategic vision, I believe in the importance of resilience, adaptability, and ethical practices. I work collaboratively to achieve organizational goals and promote sustainable growth.

Academic Interests

I am interested in artificial intelligence, machine learning, and data science, with an emphasis on developing advanced models and innovative solutions for complex problems. I continuously enhance my technical and theoretical knowledge.

Technical Skills

Experienced in languages such as Python, JavaScript, C++, and Rust, as well as machine learning frameworks like TensorFlow and PyTorch. Proficient in Linux systems, server administration, and data-driven software development.

Skills

Here are simplified rankings of my skills. A ranking of 100% does not imply unlimited knowledge of the technology; rather, it indicates that compared to other technologies listed here, I have a superior level of proficiency in this specific area.

Programming Languages

Python Python 90%
  • Backend Development
  • Data Analysis
JavaScript JavaScript 80%
  • Frontend Development
  • Node.js
TypeScript TypeScript 60%
  • Frontend Development
C++ C++ 30%
  • System Development
Rust Rust 20%
  • Systems Programming

Frameworks and Libraries

Django Django 85%
  • Web Development
  • RESTful APIs
Pandas Pandas 85%
  • Data Analysis
  • Data Manipulation
Scikit-learn Scikit-learn 75%
  • Machine Learning
  • Predictive Modeling
Ultralytics Ultralytics 70%
  • YOLO Implementation
  • Model Training

Tools, Platforms & Computer Vision

Jupyter Notebook Jupyter Notebook 85%
  • Interactive Documentation
  • Data Visualization
Git Git 90%
  • Version Control
  • Project Collaboration
Docker Docker 75%
  • Containerization
  • Development and Deployment
OpenCV OpenCV 80%
  • Image Processing
  • Object Detection
YOLOv11 YOLOv11 65%
  • Object Detection
  • Image Segmentation

AI and Scripting

TensorFlow TensorFlow 75%
  • Deep Learning
  • Model Development
PyTorch PyTorch 65%
  • Neural Network Training
  • AI Research
Hugging Face Hugging Face 50%
  • Language Models
  • NLP Implementation
NVIDIA RAPIDS NVIDIA RAPIDS 50%
  • GPU Data Analysis
  • Fast Processing
Bash Bash 70%
  • Scripting
  • Task Automation
PowerShell PowerShell 60%
  • Task Automation
  • System Management

Database and Visualization

SQL SQL 80%
  • Database Queries
  • Query Optimization
Plotly Plotly 75%
  • Data Visualization
  • Interactive Charts
APIs APIs 85%
  • Development and Consumption
  • System Integration
Data Science Data Science 85%
  • Statistics
  • Data Modeling

Operating Systems

Linux Linux 80%
  • System Administration
  • Shell Scripting
Windows Windows 75%
  • System Administration
  • Technical Support

Curriculum

Education

Bachelor's Degree in Production Engineering

2018 - 2023

Federal University of Catalão, Catalão, Goiás

The Production Engineer is responsible for ensuring the efficiency of production processes while maintaining low production costs for a company or industry.

The program is designed to provide a solid scientific, technological, and professional foundation that enables production engineers to identify, formulate, and solve problems related to project activities, operation, and management of work and production systems for goods and/or services. This encompasses human, economic, social, and environmental aspects, with an ethical and humanistic perspective, in response to societal demands.

Course Website: https://engproducao.catalao.ufg.br

Course Curriculum: https://engproducao.catalao.ufg.br/p/6444-grade

Professional Experience

Purchasing Intern at HPE Automotores do Brasil (Mitsubishi Motors Company)

2022 - 2023

Catalão, Goiás, Brazil

  • Automated the download of necessary queries for the purchasing panel, budget requests, NCM queries, and more, improving efficiency.
  • Implemented automated generation of purchase orders and real-time NCM queries using part numbers for product classification, enhancing accuracy.
  • Updated supplier cross-reference data (DE-PARA) in the company's ERP based on Excel spreadsheets, streamlining data management.
  • Developed an interface for generating appointment letter numbers from a connected database, facilitating administrative processes.
  • Implemented SERASA Scraper to extract financial data from SERASA PDF reports for the Supplier Monitoring Index (IMF), enhancing supplier evaluation.
  • Created a database for mapping network contracts from PDF files and assisted in obtaining materials and services to meet project requirements.
  • Supported the creation and evaluation of purchase orders for accuracy and compliance and actively participated in supplier negotiations.
  • Collaborated with teams for demand forecasting and stock replenishment, optimizing inventory management and procurement processes.
  • Conducted data analysis and generated reports to improve purchasing processes and provided insights on market trends and industry regulations.

Artificial Intelligence Developer at HPE Automotores do Brasil (Mitsubishi Motors Company)

Nov 2023 - Present

Catalão, Goiás, Brazil · On-site

Responsibilities:

  • Develop and implement artificial intelligence models for detection and classification of automotive components using frameworks like TensorFlow and PyTorch.
  • Design and develop the 360° Quality Inspection Station equipped with high-resolution cameras and computer vision systems for comprehensive vehicle inspection.
  • Create advanced image processing and object detection algorithms to analyze captured images and identify specific vehicle components.
  • Compare obtained data with predefined standards stored in JSON files, ensuring compliance with specifications of each vehicle model.
  • Develop intuitive graphical interfaces for presenting results on monitors in the inspection line, facilitating data interpretation by the team.
  • Implement the Sealant Inspection Station using overhead cameras to map and verify the correct application of 108 sealant points on benches.
  • Manage technological innovation projects from conception to implementation, including planning, scheduling, and coordination with multidisciplinary teams.
  • Utilize data science and machine learning techniques for data analysis and continuous improvement of developed systems.
  • Automate web and local processes to optimize workflows and increase operational efficiency.
  • Collaborate with internal teams to identify needs and propose innovative technological solutions.
  • Develop strategic and communication skills to present projects and results to stakeholders and senior management.

Skills and Competencies:

  • Proficiency in Python and AI frameworks like TensorFlow and PyTorch.
  • Experience in computer vision and image processing with OpenCV and YOLO.
  • Knowledge in software development and system integration.
  • Skills in process automation and web development with Django.
  • Ability to perform statistical analyses and apply data science techniques.
  • Experience in project management and technical leadership.
  • Excellent communication skills and teamwork.
  • Capacity for innovation and strategic thinking.

Practical Projects

360° AI Inspection Station

Project that presents an innovative automotive quality inspection station utilizing artificial intelligence and high-resolution cameras. The station is equipped with four cameras positioned on the sides and the front and rear of the vehicle, which move synchronously to obtain a comprehensive 360° view of the vehicle.

The collected images are processed by an object detection algorithm that identifies and analyzes specific components of the vehicle. The obtained data is compared with pre-defined standards stored in JSON files containing detailed information about each vehicle model (obtained from the VIN number).

The final results are presented on a graphical interface displayed on a 65" monitor on the quality inspection line. This inspection method ensures accurate and efficient verification, reducing human errors and improving the consistency of the final product's quality. The integration of AI allows for an agile and reliable process, making the station a robust solution for the automotive industry.

AI Inspection Station
Complete Inspection Station
Vehicle Segmentation
Vehicle Segmentation
Motor Components Detection
Motor Components Detection
Inspection Results
Inspection Results Dashboard

Sealant Inspection Station with Artificial Intelligence

Development of an inspection station that uses an overhead camera to map 108 sealant points on a bench, verifying if all are present, in the correct position, and of the appropriate size. The system ensures quality in the application of sealant, guaranteeing compliance with established standards.

Sealant Bench
Sealant Application Bench
Inspection Example
Sealant Inspection in Action

Restaurant Entry People Counting System

Development of an AI-based system for counting people entering the company restaurant during peak morning hours. While turnstiles are used during regular periods, they become impractical during high-traffic morning times. The AI solution counts individuals accurately to ensure proper billing per meal, eliminating bottlenecks and improving flow efficiency.

Drone-Based Yard Mapping and Vehicle Counting

A prototype demonstrating the capabilities of aerial AI vision using drones for mapping and object identification. This solution enables efficient counting and identification of vehicles across multiple yards. The system provides real-time inventory management, eliminating the need for manual counting and offering an overhead perspective that improves accuracy and data collection efficiency.

AI-Based Value-Added Analysis (AVA)

Implementation of an intelligent video inspection system that automatically categorizes manufacturing processes into three categories: value-adding, non-value-adding, and incidental activities. This AI-powered solution enables detailed process analysis, identifies improvement opportunities, and enhances production efficiency by providing objective, data-driven insights into workflow optimization.

Certificates

Python 3 Course from Basic to Advanced - with Real Projects, Udemy
January 7, 2022
  • Basic Python 3 (with programming logic)
  • Intermediate Python 3 (with procedural and functional programming)
  • Advanced Python 3 (with object-oriented programming)
  • Python modules, such as PySide6 for GUI with Qt 6, Selenium, Django, and more
  • Django for creating websites and APIs
  • Relational databases: SQLite3, MySQL, and MariaDB
  • Automated testing in Python (with basic TDD)
  • Design patterns (GoF Design Patterns)
  • Extra: Regular Expressions
  • Extra: HTML5 and CSS3
  • Extra: SQL with MySQL
  • Extra: Unix Commands (Linux, Mac, and Windows WSL2)
  • Course with guaranteed updates by the instructor
    • Duration: 112 hours
    Pratical Deep Learning With TensorFlow and Python, Udemy
    January 7, 2022
  • Build simple perceptrons to convert temperatures from Celsius to Fahrenheit
  • Use regression to predict ice cream sales, house prices, and bike rentals
  • Construct neural networks for sentiment analysis using text datasets
  • Classify traffic signals from images with convolutional neural networks
  • Utilize transfer learning for object classification
  • Use the pre-trained LeNet neural network to classify images
  • Build autoencoders to denoise and compress images
  • Learn the theory and practice of the Deep Dream algorithm to generate hallucinogenic images
  • Automatically generate text using recurrent neural networks
  • Create new images that have never existed before using generative adversarial networks (GANs)
    • Duration: 15 hours
    Machine Learning and Data Science with Python from A to Z, Udemy
    January 7, 2022
  • Classification - data preprocessing, naive Bayes, decision trees, random forest, rules, logistic regression, support vector machines (SVM), artificial neural networks, algorithm evaluation, and classifier combination and rejection
  • Regression - simple and multiple linear regression, polynomial regression, decision trees, random forest, support vector regression (SVR), and artificial neural networks
  • Association rules - Apriori and ECLAT algorithms, Clustering - k-means, hierarchical clustering, and DBSCAN
  • Additional topics - dimensionality reduction with PCA, KernelPCA, and LDA, outlier detection, reinforcement learning, natural language processing, computer vision, handling imbalanced data, attribute selection, and time series forecasting
    • Duration: 42 hours
    Statistics for Data Science and Machine Learning, Udemy
    January 7, 2022
  • Key statistical concepts and calculations for Data Science and Machine Learning
  • Step-by-step implementation of statistics and probability in Python
  • Relationship between Statistics, Data Science, and Machine Learning
  • Sampling techniques: simple, systematic, stratified, cluster, and reservoir
  • Theory and practice of main Machine Learning algorithms and their statistical connections
  • Handling imbalanced data with sampling techniques in Machine Learning
  • Calculating percentages, indices, coefficients, and rates
  • Frequency distributions and histograms for data visualization
  • Measures of central tendency: mean, mode, median, quartiles, and percentiles
  • Measures of data dispersion: range, variance, standard deviation, coefficient of variation
  • Using central tendency and dispersion measures to evaluate Machine Learning algorithms
  • Handling missing data with central tendency measures
  • Using variance to select the best features in a dataset
  • Main statistical and probability distributions: normal, gamma, exponential, uniform, Bernoulli, binomial, Poisson
  • Inferential statistics for probability calculations
  • Confidence intervals and hypothesis testing
  • Hypothesis tests: ANOVA, Chi-Square, Wilcoxon, Friedman, Nemenyi
  • Calculating variable correlation
  • Creating linear regression models for number prediction
  • Generating graphs and maps for data interpretation
    • Duration: 20 hours
    GOOGLE Foundations of Data Science, Coursera
    January 7, 2022
  • Introduction to data science concepts and methodologies
  • Data manipulation and analysis using Python
  • Data visualization techniques for effective communication
  • Statistical analysis and inference
  • Exploratory data analysis (EDA) and data cleaning
  • Introduction to machine learning and predictive modeling
  • Working with real-world datasets and case studies
  • Using SQL for data extraction and management
  • Implementing data science projects from start to finish
  • Collaborating and sharing results using data science tools
    • Duration: 15 hours
    GOOGLE Get Started With Python, Google Developers
    January 7, 2022
  • Introduction to Python programming language
  • Setting up the development environment
  • Basic syntax, data types, and variables
  • Control structures: loops and conditionals
  • Functions and modular programming
  • Working with libraries and modules
  • Basic data structures: lists, dictionaries, and sets
  • File handling and I/O operations
  • Error handling and exceptions
  • Introduction to web development with Python
  • Building simple applications and scripts
    • Duration: 15 hours
    GOOGLE Go Beyond the Numbers: Translate Data into Insights, Coursera
    January 7, 2022
  • Understanding the importance of data-driven decision making
  • Techniques for cleaning and preparing data
  • Exploratory data analysis (EDA) to discover patterns and insights
  • Data visualization principles and best practices
  • Using visualization tools to create impactful charts and graphs
  • Statistical analysis for interpreting data
  • Identifying trends and outliers in data
  • Communicating findings effectively to stakeholders
  • Case studies and real-world examples of data insights
    • Duration: 15 hours
    Data Science for Businesses and Enterprises, Udemy
    May 6, 2022
  • Human Resources Department: Development of an AI model to reduce hiring and employee training costs, predicting which employees may leave the company.
  • Marketing Department: Optimization of marketing strategy through customer segmentation.
  • Sales Department: Implementation of time series forecasting to predict future product prices.
  • Medical Department: Development of a Deep Learning model to automate and optimize disease detection processes in a hospital, using X-ray images.
  • Public Relations Department: Creation of natural language processing models to analyze customer comments on social media for sentiment identification.
  • Production and Maintenance Departments: Development of neural networks to detect defects in parts and locate defects in faulty components.
    • Duration: 14.5 hours
    Web Master Course Complete Front-End, Danki Code
    2021

    Web Development, HTML, CSS, Javascript, Bootstrap

    Validation Code: ff422b6a-affd-4f83-bac2-7fbdebe6f327

    Duration: 81 hours
    Advanced Basic Excel 5 Courses - Specialist Training, Udemy
    February 20, 2022

    Advanced Excel Functions, Pivot Tables, Dashboards, Power Query, Macros, VBA, Goal Seek and Solver, Final Project

    Duration: 42 hours

    Resources to Learn Programming (Focused on Python and AI)

    1. FreeCodeCamp – Free YouTube Channel (English)

      Great for general computing and programming content. Has complete courses, tutorials, and practical projects in various languages, including Python.

      FreeCodeCamp YouTube Channel

    2. Curso em Vídeo – Python Fundamentals (Portuguese)

      Excellent introductory course for beginners, with clear teaching and practical exercises.

      • Python World 1 (Basic) → World 2 (Intermediate) → World 3 (Advanced)

      Curso em Vídeo Website

    3. Udemy – Complete and Affordable Courses

      Highly structured courses, often on promotion (R$ 20–30). Recommendations:

      • Python 3 from Zero to Advanced (Luiz Otávio)

      Python 3 Course

      • Machine Learning and Data Science with Python (Promotion with coupon)

      Machine Learning Course

    4. Exercism – Practice Fundamentals (English)

      Interactive platform to learn languages by solving exercises with community feedback.

      Exercism Website

    5. Artificial Intelligence as a Learning Tool

      Models like DeepSeek-V3, ChatGPT (OpenAI), Claude 3, Gemini (Google), Qwen & Grok can:

      • Explain programming concepts.
      • Generate code examples on demand.
      • Help solve doubts in real time.

      Recommendation: Use them initially for study and, after consolidating the basics, for productivity.

    6. Books (Optional for Deepening Knowledge)

      Books are useful for structured approaches and specific topics. Examples:

      • Clean Code (Robert C. Martin) – Good programming practices.
      • Python Crash Course (Eric Matthes) – Practical introduction.

    Additional Notes

    • English is essential to access documentation, forums, and advanced content.
    • Official documentation (Python, TensorFlow, PyTorch, etc.) should be consulted for technical reference.