Knowledge Representation in Oil & Gas
Processes in Oil & Gas business are knowledge intensive, having singular needs for knowledge representation and processing. In this talk, I will specifically discuss a multimodal knowledge representation framework tailored for the Oil & Gas domain as well as some aspects related to knowledge-based machine learning. I will also give a brief overview of KR tools being developed at IBM Research Brazil to tackle some of these problems.
About the speaker
Sandro Rama Fiorini is Research Staff Member at IBM Research, Rio de Janeiro, Brazil. Sandro received his PhD in Computer Science from the Federal University of Rio Grande do Sul (UFRGS), Brazil, in collaboration with Lund University, Sweden. His research interests include Knowledge Representation and Ontologies applied to Robotics and Automation, being also active in research applied to Petroleum Geology. Sandro is also vice-chair of the EDARR Working Group, currently in charge of developing the IEEE P7007 – Ontological Standard for Ethically Driven Robotics and Automation Systems. Sandro has also been one of the key members of the IEEE Ontology for Robotics and Automation Working Group, which developed the IEEE 1872-2015 standard. Previous work experience includes 2.5 years as a lecturer at the Pontifical Catholic University of Rio Grande do Sul (PUC-RS) and 2 years as a postdoc researcher at Universite Paris-Est Creteil, France.