Jaqueline Vianna

Collaborating Researcher at the Nuclear Engineering Institute (IEN) of the National Nuclear Energy Commission (CNEN), assistant professor of the Graduate Program in Nuclear Science and Technology of the Nuclear Engineering Institute (PPGIEN), collaborating researcher and assistant professor of the Fuzzy Logic and Mathematics (LabFuzzy) from the Production Engineering Program (PEP) at COPPE/UFRJ, Researcher at ResiliSUS - Study Group on Management, Social Technologies and Information for Resilience in Public Health, based at the Center for Strategic Studies of the Foundation Oswaldo Cruz (CEE/FIOCRUZ). PhD student in Production Engineering at COPPE/UFRJ, Doctoral Extension at Universidade Federal do Sul (in Russian: Южный федеральный университет) in Complex Systems Engineering (2022), Master in Nuclear Science and Technologies at the Institute of Nuclear Engineering (IEN), at National Nuclear Energy Commission (CNEN) (2021) that won the award for the best dissertation of the year 2021, from the Brazilian Congress of Knowledge Management - KM Brasil 2022. The annual event is directed and held by SBGC - Brazilian Society of Knowledge Management and Nuclear Ambassador for the Brazilian Association of Nuclear Energy - ABEN. Graduate in Public Governance and Sustainability from UNINTER Centro Universitário (2019) and Graduate in Civil Engineering (2007). In 04/2021, he participated in the idealization and implementation of the Knowledge Engineering Laboratory (LABEC) of IEN/CNEN and since then manages LABEC. He develops research in collaboration with COPPE/PEP (UFRJ), the Institute of Studies in Collective Health at UFRJ (IESC/UFRJ), the Carlos Chagas Filho Institute of Biophysics at UFRJ (IBCCF/UFRJ), the Postgraduate Program in Production Engineering at the Federal University of Rio Grande do Norte (PEP/UFRN) and the Graduate Program in Tropical Medicine (PPGMT) at the State University of Amazonas (UEA). His research focuses on knowledge engineering of institutions that deal with complex systems through mathematical models of decision-making and hierarchization.