- PUC-Rio
- Seals
- University College London
Resume
Education and academic position
- PhD in Computer Science, University College London, 1992.
- MSc in Electrical Engineering, Pontifical Catholic University of Rio de Janeiro, 1987.
- BSc in Electrical Engineering, Pontifical Catholic University of Rio de Janeiro, 1985.
- Associate Professor (Electrical Engineering Department, PUC-Rio)
- Past Supervision: (21) Ph.D. Thesis and (52) M.Sc. Dissertations
Courses
Undergraduate
- Inteligência Computacional Aplicada(Applied Computational Intelligence)
Post-graduate
- Redes Neurais I (Neural Networks I)
- Redes Neurais II (Neural Networks II)
- Lógica Fuzzy (Fuzzy Logic)
- Sistemas Inteligentes Aplicados (Applied Intelligent Systems)
Awards
- Petrobras Technology Award 2008; Category: Undergraduate on the theme Security and Operation Performance Technology - "Caracterização da Confiabilidade Humana nas Atividades de Operação, Manutenção e Inspeção em Refinarias de Petróleo", undergraduate student Nicholas Pinho Ribeiro, supervised by Profs. Ricardo Tanscheit and Marley Vellasco, ICA: Applied Computational Intellingence Lab, Department of Electrical Engineering, PUC-Rio.
- Petrobras Technology Award 2007; Category: PhD Thesis on the theme Perfuration and Production Technology - "Sistema de Apoio à Decisão para Uso de Poços Inteligentes no Desenvolvimento de Reservatórios de Petróleo", PhD student: Luciana Faletti Almeida, supervised by Profs. Marley Vellasco and Marco Aurélio Pacheco, ICA: Applied Computational Intellingence Lab, Department of Electrical Engineering, PUC-Rio.
- 3rd place on The 4o Mostra PUC-Rio/Petrobras, Category: Technical/Cientific: “Estação Meteorológica de Baixo Custo”, 21 August 2007.
- 2nd place on Petrobras Technology Award 2005; Category: Oil Recuperation Technology - "EXPLOT - Sistema de Apoio à Decisão para Otimização da Explotação de Petróleo", students: Yván Jesús Túpac Valdivia and Luciana Faletti, supervised by Profs. Marley Vellasco and Marco Aurélio Pacheco, ICA: Applied Computational Intellingence Lab, Department of Electrical Engineering, PUC-Rio.
ICA: Applied Computational Intelligence Lab (site)
Intelligent Systems refer to an assortment of computerized technology that aims at supporting the management and the process of decision making: Neural Networks, Genetic Algorithm, Fuzzy Logic, Expert Systems, Hybrid Systems, Statistical Models, Stochastic Processes, Real Options and Multiple Criteria Optimization Methods.
The Intelligence in business consolidates and analyses business data, transforming them in useful and conclusive information. It allows companies to find information, in different data sources, about their clients, transactions and markets – and use them to attain a competitive profit. The Intelligence offers to the companies the necessary systems and information to identify new tendencies, relationship improvement, process optimization, problem solving, reduction of financial risks and generation of new business opportunities.
Intelligent systems have been successfully applied in forecasting, optimization, risk analysis, control, inference, modeling and fraud detection, in a wide range of knowledge fields. These systems offer comprehensive solution for managers and decision makers to a large number of complex and extensive applications that are considered difficult, totally limited or even impossible by companies in different business fields: Economy and Finance, Trade and Commerce, Engineering, Energy, Transport, Logistic, Marketing, Environment, Medicine, etc.
- Costs Reduction
- Increasing of productivity
- Better use of resources