Master’s student in Agricultural Engineering at UNESP, focused on machine learning for anomaly detection in solar irradiance time series. CNPq scholarship recipient with experience in Big Data, ETL pipelines, and time series analysis.
🔐 Patent co-inventor • 📰 Author/co-author of 5+ papers • 🎓 Azure- and Google Cloud-certified
Languages: Python • Java • C++ • SQL
ML/Data: TensorFlow • Pandas • Scikit-learn • NumPy
Cloud/Data Engineering: Azure • Google Cloud • Docker
- Solar Irradiance ML Pipeline — Machine learning pipeline for detecting extreme events in solar irradiance time series.
- Big Data ETL — Production pipeline for large-scale solar measurement data using Python and Azure.
- Computer Vision — Recyclable waste classification project using Azure AI.
- IoT Monitoring System — Real-time UV radiation monitoring system related to patent BR512026000933.
Bridging Machine Learning and Agricultural Science