Summary
Rodrigo Rosa is an AI researcher with nine years of experience bridging signal processing and machine learning to deliver industry-ready solutions. With a Master's in Signal Processing and Machine Learning from UFSC, he has applied deep learning and classical ML to predictive maintenance, anomaly detection, and forecasting across automotive, HVAC-R, and gas sectors. He currently researches embedded-system AI at Instituto SENAI de Inovação, having previously built production ML pipelines, ETL workflows, and monitored deployed models using MLOps practices. Comfortable with Python and convolutional models for vibration data, Rodrigo combines academic rigor with hands-on deployment experience, and he often works on real-world datasets and public benchmarking to validate solutions. An understated strength is his ability to translate noisy sensor signals into robust features and scalable models that improve industrial efficiency.
8 years of coding experience
4 years of employment as a software developer
Master's degree, Signal Processing and Machine Learning, Master's degree, Signal Processing and Machine Learning at Universidade Federal de Santa Catarina
Portuguese, English, Japanese