Wilgo Moreira Nunes Cardoso received his BEng in Mechanical Engineering in 2008 from the Federal University of Ceara (Brazil). He then completed a Master’s degree in 2012 at the Federal University of Uberlandia (Brazil), specializing in mechatronics and cable-driven rehabilitation robotics. In 2023, he began his PhD in Electrotechnical Engineering and Intelligent Systems at the University of Coimbra, where he is currently a doctoral fellow funded by the Foundation for Science and Technology (FCT). To date, Wilgo has authored 7 peer-reviewed conference publications. His Master’s degree has been officially recognized in Portugal with a final classification of 18 out of 20. Currently, he investigates deep learning-based perception for agricultural robotics, with an emphasis on uncertainty-aware models and probabilistic segmentation techniques using multispectral data. Complementing his doctoral research, he recently completed a research internship at the National Laboratory for Civil Engineering (LNEC), where he developed an advanced fault detection system for Structural Health Monitoring (SHM) sensor networks. This project involved applying time-series modeling with Facebook Prophet and physics-based feature engineering (solar vector) to create a robust, adaptive statistical control system for real-world bridge sensor data. Beyond his academic experience, Wilgo brings over ten years of engineering experience, having held technical leadership positions at Petrobras Distribuidora S.A. and the Brazilian Hospital Services Company (EBSERH). In these roles, he coordinated multidisciplinary engineering projects in automation, sustainability, and HVAC systems, including critical interventions during the COVID-19 pandemic. In his early doctoral work, he has already co-authored and presented papers at international conferences (e.g., ROBOT 2024, ICIR 2024). He maintains an active presence in the open science community through his GitHub profile (github.com/wilgomoreira), where he shares projects in machine learning, image segmentation, and robotics. Wilgo currently collaborates with the VESTA project, coordinated by the SME SpotLite, where he has been developing new approaches on supervised classification using satellite imagery and machine learning.