At State University of Ponta Grossa, I lead a CNPq-funded research team building predictive pipelines for complex neural time series, from preprocessing and feature engineering through modeling and evaluation. I develop and benchmark approaches to detect regime changes and forecast candidate critical transitions.
Across industry collaborations, I delivered AI and machine-learning solutions in pharmaceutical, financial, biomedical, and industrial domains. One sensor-based failure prediction model reached 92% recall, and I’ve also built a domain-grounded RAG pipeline for regulated pharmaceutical content. My work draws on 14 years of experience across computational engineering, data pipelines, scientific software, and applied AI/ML, and includes 50 peer-reviewed publications.
