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Márcio Porto Basgalupp

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Universidade Federal de São Paulo (UNIFESP). Campus São José dos Campos. Instituto de Ciência e Tecnologia (ICT)  (Institutional affiliation for the last research proposal)
Birthplace: Brazil

has graduation at Bacharelado at Ciência da Computação by Universidade Federal de Pelotas (2007), master's at Ciência da Computação by Pontifícia Universidade Católica do Rio Grande do Sul (2009), and Ph.D. at Ciências da Computação e Matemática Computacional by Universidade de São Paulo (2013). Currently is Associate Professor at Institute of Science and Techonology at Federal University of Sao Paulo (UNIFESP). Has coordinated national and international research projects funded by CNPq and FAPESP. Has experience in the area of Computer Science, with emphasis on Machine Learning, Data Mining and Bio-inspired Computation. Since 2014, is granted by CNPq with a Research Productivity Award. (Source: Lattes Curriculum)

Research grants
Scholarships in Brazil
Scholarships abroad
FAPESP support in numbers * Updated February 15, 2020
Total / Available in English
Most frequent collaborators in research granted by FAPESP
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Use this Research Supported by FAPESP (BV/FAPESP) channel only to send messages referring to FAPESP-funded scientific projects.


 

 

 

 

Keywords used by the researcher
Scientific publications resulting from Research Grants and Scholarships under the grantee's responsibility (3)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

Publications3
Citations21
Cit./Article7.0
Data from Web of Science

DAL PICCOL SOTTO, LEO FRANCOSO; DE MELO, VINICIUS VELOSO; BASGALUPP, MARCIO PORTO. -LGP: an improved version of linear genetic programming evaluated in the Ant Trail problem. KNOWLEDGE AND INFORMATION SYSTEMS, v. 52, n. 2, p. 445-465, . Web of Science Citations: 2. (13/20606-0, 16/07095-5)

BARROS, RODRIGO C.; BASGALUPP, MARCIO P.; DE CARVALHO, ANDRE C. P. L. F.. Investigating fitness functions for a hyper-heuristic evolutionary algorithm in the context of balanced and imbalanced data classification. Genetic Programming and Evolvable Machines, v. 16, n. 3, p. 241-281, . Web of Science Citations: 1. (09/14325-3)

BARROS, RODRIGO C.; BASGALUPP, MARCIO P.; FREITAS, ALEX A.; DE CARVALHO, ANDRE C. P. L. F.. Evolutionary Design of Decision-Tree Algorithms Tailored to Microarray Gene Expression Data Sets. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, v. 18, n. 6, p. 873-892, . Web of Science Citations: 18. (09/14325-3)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

BASGALUPP, Márcio Porto. LEGAL-Tree: um algoritmo genético multi-objetivo para indução de árvores de decisão. 2010. Tese (Doutorado) – Instituto de Ciências Matemáticas e de Computação. Universidade de São Paulo (USP). São Carlos.

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