Projeto : Modelo de Integração de Dados para o setor de Urologia
Grupo de Pesquisa: Data Space aplicada a Saúde
O modelo de referência para o design de repositório de dados de saúde é aplicado para o setor de urologia, tendo como referência o ReSKU (Registry for Stones of the Kidney and Ureter), em parceria com o Hospital Universitário da USP, através do seu Núcleo de Inovação e Tecnologia (INTEC), e com outros parceiros que devem confirmar em breve sua participação. Conta ainda com a colaboração com o Hospital Universitário e Faculdade de Medicina da Universidade do Alabama, EUA.
Atualizado em
19 de Novembro de 2025, 16:06
Pesquisador Responsável
Jose Reinaldo Silva
reinaldo@usp.brBachelor in Physics from Bahia Federal University, got aMSc in Physics from Pernanbuco Federal University UFPE, and a MA in Computer Science from Mills College, USA. PhD in Computer Engineering by Universith of São Paulo and postdoc in Computer Science and in Systems Design Engineering at University of Waterloo, Ca. Research interests are in Engineering Systems Design, Requirements Engineering, Service Design Management and Engineering, Artificial Intelligence, Planning & Scheduling, Formal Verification methods, Data Spaces and Digital Transformation towards Industry 4.0.
Colaboradores
Elinilson Vital
vital@usp.brMaster's student in Mechatronics Engineering at the Polytechnic School of the University of São Paulo, focusing on the theme Cloud Manufacturing Services (CMfgS): Modeling of automated production systems in the cloud. Graduated in Applied Mathematics in Mechanical Control and Automation from the Institute of Mathematics and Statistics of the same university, focusing on formal requirements analysis, service science, distributed systems, knowledge bases, and data spaces. Demonstrates ability to apply mathematical and computational knowledge to solve complex problems and promote technological innovations. Practical experience includes data science, data grouping and their applications, as well as in modeling and analysis of automation systems, also in programming and simulation, including algorithms and data structures, concurrent and parallel programming, and numerical methods for differential equations. The main research interests are currently focused on deepening knowledge in Service Science and Data Spaces, aiming to develop innovative solutions that optimize business processes and increase technological efficiency in distributed environments, uniting mathematics, computing, and engineering.
