Summary
Witenberg Souza is a Machine Learning Engineer with eight years of experience applying data-driven models to real-world problems, from methane leak detection at JPL to high-accuracy pest classification for agriculture. He combines a strong academic foundation in mechatronics and electrical engineering with hands-on skills in Python, TensorFlow, PyTorch, FastAI and MATLAB, and practical experience in product design, project management and teaching. Notable projects include a MATLAB image corruption/recovery pipeline and a 97%‑accurate corn pest classifier built on a novel 700+ image dataset, demonstrating his ability to move prototypes into measurable outcomes. He has experience generating synthetic time-series simulations and stochastic decision maps for drone-based environmental monitoring, showing an aptitude for combining simulation, feature engineering and deployed ML. Comfortable mentoring and presenting research, he bridges academia and applied engineering to deliver solutions that increase productivity across industries.
8 years of coding experience
3 years of employment as a software developer
Non-Dregree Electrical and Electronics Engineering, Non-Dregree Electrical and Electronics Engineering at Illinois Institute of Technology
Master's degree Electrical Electronics and Communications Engineering, Master's degree Electrical Electronics and Communications Engineering at Northern Illinois University
Bachelor's degree ElectricalCommunications Engineering, Bachelor's degree ElectricalCommunications Engineering at IESB
Master of Science - MS Mechatronics Robotics and Automation Engineering, Master of Science - MS Mechatronics Robotics and Automation Engineering at Universidade de Brasília
Computer Science, Computer Science at Serzedello Corrêa Institute, Audit Court
Portuguese, English, Spanish, Dutch, French, German, Japanese, Korean