CV Lattes
Universidade Federal de São Paulo (UNIFESP). Campus São José dos Campos. Instituto de Ciência e Tecnologia (ICT) (Institutional affiliation from the last research proposal) Birthplace: Brazil
Bachelor in Computer Science at Federal University of Sao Paulo (2015) and PhD in Computer Science at Federal University of Sao Paulo (2020). During this time, obtained experience in the areas of Evolutionary Computation applied to Machine Learning problems (regression, classification, feature construction), automatic design of digital circuits, evolution of intelligent agents, and estimation of distribution algorithms. Since 2020, works as a postdoc and research scientist at the Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), where he investigates the application of evolutionary algorithms and transfer learning to computer-integrated manufacturing (CIM). Interested in the areas of Evolutionary Computation, Machine Learning, representations for Genetic Programming, Estimation of Distribution Algorithms, Transfer Learning, and applications. (Source: Lattes Curriculum)
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Linear Genetic Programming is a type of algorithm able to evolve code in a programming language. LGP has been applied in a wide range of problems, as machine learning, navigation, and routing. Its stochastic search process has no knowledge to generate good solutions nor is able of avoiding poor ones, which decreases its efficiency. In this project, two topics will be explored in order to …
This project aims to study the application of evolutionary algorithms - Genetic Programming initially - in the automatic evolution of behavior trees of an intelligent agent, which determine the actions to be taken in accordance with the current configuration of the environment. The intelligent agent that will be studied in this project is an implementation in the framework for study of ar…
Linear Genetic Programming (LGP) is a kind of algorithm capable of evolving computer code which has been successfully applied in various problems, such as Machine Learning (ML), navigation, and routing. As in other Evolutionary Algorithms (EAs), its stochastic search process neither has the knowledge to produce good quality solutions nor is able to avoid poor quality solutions, which redu…
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