Ph.D. Candidate in Electrical Engineering | AI Researcher | Software Developer
I'm a Ph.D. candidate with experience in two research institutions, Unifei and Inatel. Currently, I am pursuing a Ph.D. in Electrical Engineering at the Federal University of Itajubá (UNIFEI), where my research focuses on Neural Architecture Search (NAS) for EEG-based deep learning models targeting resource-constrained embedded devices. My work investigates hardware-aware optimization techniques for designing efficient neural networks capable of performing intelligent signal analysis in low-power edge computing environments.
During my time at the Instituto Nacional de Telecomunicações (INATEL), I conducted research on decentralized learning approaches based on Federated Learning and Blockchain, exploring distributed architectures for privacy-preserving and collaborative AI systems. Additionally, during my Master’s research, I investigated IoT-based solutions for agriculture using LoRa communication technologies, focusing on low-power wireless networks for Computer Vision and Machine Learning models, edge-enabled sensing, and smart monitoring systems for agricultural applications.
My background spans Engeneering, Computer Science, Data Science and Artificial Intelligence System, providing a multidisciplinary foundation for developing AI-driven solutions at the intersection of Edge AI, IoT, and distributed intelligence.
| AI & Agents |
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| Backend & Cloud |
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| Data Eng & MLOps |
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| 📄 Advances in the Use of rPPG for Non-Invasive Heart Rate Estimation SBrT, 2025 |
📄 Brain Tumor Detection Using YOLOv11 on Edge Computing for Decision Support ACDSA, 2025 |
| 📄 Enhancing Healthcare Through Collaborative Intelligence: a Federated Learning Case Study IEEE LASCAS, 2025 |
📄 A Federated Learning-based Solution for Pneumonia Diagnosis in Remote and Low-Income Areas SBrT, 2024 |
| 📄 Brain Tumor Images Class-Based and Prompt-Based Detectors and Segmenter: Performance Evaluation of YOLO, SAM and Grounding DINO ICoABCD, 2024 |
📄 Pick and Place em Tempo Real Usando Visão Computacional com YOLOv8 e Staubli TS60 SBrT, 2024 |
| 📄 Application of YOLOv7 for Real-Time Detection of Aedes Aegypti SBrT, 2023 |
📄 A Multi-Faceted Approach to Maritime Security: Federated Learning, Computer Vision, and IoT in Edge Computing SBrT, 2023 |
| 📄 Evaluating Computer Vision Architectures for Ship Classification: A Comparative Study SBrT, 2023 |
📄 Smart Farming with Computer Vision: Detecting Diseases in Strawberry Crops via Mobile Applications SBrT, 2023 |
| 📄 Design, Deployment, and Validation of a Low-Cost IoT Platform based on LoRa for Precision Dairy Farming SBrT, 2023 |
📄 Vehicle and Plate Detection for Intelligent Transport Systems: Performance Evaluation of Models YOLOv5 and YOLOv8 IEEE ICOCO, 2023 |
| 📄 An IoT Crop Recommendation System with k-NN and LoRa for Precision Farming SBrT, 2022 |
📄 Design, Application, and Validation of an IoT Wireless Sensor Network based on LoRa for Strawberry Farming SBrT, 2022 |
| 📄 Smart Strawberry Farming Using Edge Computing and IoT SENSORS, 2022 |