Lucas Cardoso
Software Engineer | Computer vision & AI
MSc in Computer Engineering • Founder @ Green Next & Zenith Softworks
Software Engineer | Computer vision & AI
MSc in Computer Engineering • Founder @ Green Next & Zenith Softworks
Automation and Computer Engineer with 5+ years of experience developing Artificial Intelligence and Computer Vision solutions. Specialized in object detection with YOLO, image processing, and development of production-ready Machine Learning pipelines.
Currently pursuing a Master's degree in Computer Engineering, with research focused on Deep Learning applied to computer vision. As Founder & CEO of Green Next, I lead the development of sustainable technology solutions using AI for industrial and environmental process optimization.
Object detection, segmentation, OCR, real-time image and video analysis
YOLO, CNNs, Transfer Learning, PyTorch, TensorFlow, custom model training
System integration, APIs, data pipelines, industrial automation and Python processes
Exploratory analysis, predictive modeling, data visualization, ML in production
Delta Maquinas Têxteis
Development of intelligent automation solutions with Python and AI. Building Computer Vision pipelines for fabric defect detection, achieving over 80% accuracy.
Founder and lead engineer for Data Science, AI and Computer Vision projects. Development of custom solutions for corporate clients using cutting-edge technologies.
Leading the development of AI solutions for sustainability. Implementation of Computer Vision systems for environmental monitoring and industrial process optimization with YOLO and Deep Learning.
Image classification with HOG + SVM for Deep Learning and Computer Vision.
SVM model for binary classification of heart diseases with high accuracy.
Linear Regression implementation with Stochastic Gradient Descent.
Streamlit app integrated with Google Sheets for workout tracking.
Federal University of Rio Grande - FURG
Provisional title: "Modeling and Simulation of Irrigation in Rice Cultivars". Supervised by Prof. Dr. Adriano Velasque Werhli. Development of a predictive model that simulates the dynamics of the irrigation process in rice cultivars using data from Green Next's Hydra equipment, aiming at optimizing water and energy resources in agriculture.
Federal University of Rio Grande - FURG
Thesis: "Experimental analysis of LoRa technology for remote sensing in rural properties". Supervised by Prof. Dr. Vitor Irigon Gervini. The work experimentally analyzed LoRa technology to create sensor networks in rural properties, with point-to-point communication tests at distances between 240m and 12km, proving viability for automated irrigation and real-time monitoring in agribusiness.