Summary
Antonioni Campos is a data science researcher and engineer with nine years of experience applying machine learning and deep learning to complex problems in the oil & gas industry. Trained as a mechanical engineer (UFPE) with advanced studies in Business Intelligence (PUC-Rio) and a master's in Computational Intelligence (UFRJ), he bridges physical-domain knowledge and modern AI methods. At CENPES/Petrobras he develops production-grade Data Science solutions—ranging from failure detection with probabilistic models to NLP-driven inspection-quality assessment—integrating Python backends with PI Systems, PostgreSQL/MongoDB and workflow orchestration tools. He combines research rigor with practical software engineering, deploying models into cloud and real-time process environments. Notably, his master's work on neural-network phase-equilibrium analysis demonstrates a track record of translating academic research into industry-relevant tools. Open to collaboration, he focuses on AI applications that deliver measurable operational impact.
9 years of coding experience
Graduação, Mechanical Engineering, Graduação, Mechanical Engineering at Universidade Federal de Pernambuco
Mestrado, Engenharia Elétrica, Inteligência Computacional, Mestrado, Engenharia Elétrica, Inteligência Computacional at UFRJ - Universidade Federal do Rio de Janeiro
Mestrado, Business Intelligence, Mestrado, Business Intelligence at ICA - Lab. de Inteligência Computacional da PUC-Rio
Portuguese, English