Background

I received a B.Sc. degree in Computer Science from the Federal University of Rio Grande do Norte (UFRN), Brazil, in 1991, the M.Sc. degree in Computer Science from the Federal University of Pernambuco (UFPE), Brazil, in 1995, and the Ph.D. degree in Electrical Engineering (Artificial Intelligence) from the Imperial College (London), UK, in 1999. I worked as a visiting professor at the Center of Informatics (CIn) of the UFPE for three years and, from 2002, I stayed one year as a researcher at the Institute of Mathematics and Computing (ICMC) of the University of São Paulo (USP-São Carlos, Brazil). In 2004, I joined, as an associate professor, the Department of Informatics and Applied Mathematics (DIMAp) of the UFRN. I spent one year as a visiting researcher at the Department of Computational Biology of the Max Planck Institute of Molecular Genetics, Berlin, Germany. Currently, I am a full professor at the Laboratoire d'Informatique Fondamentale d'Orléans (LIFO) at the University of Orléans (France).

Research topics

Machine Learning, Supervised Learning, Cluster Analysis, Hybrid Intelligent Systems, Bioinformatics

Selected publications

  • h-index: 18, i10-index: 35, google scholar – November 4th, 2019 (google scholar profile)
  • Ana C. Lorena, Luís P. F. Garcia, Jens Lehmann, Marcilio C. P. de Souto, and Tin Kam Ho. 2019. How Complex Is Your Classification Problem?: A Survey on Measuring Classification Complexity. ACM Computing Surveys 52, 5, Article 107 (September 2019), 34 pages.
  • Vanessa Antunes, Tiemi Sakata, Katti Faceli, and Marcilio C. P. de Souto. 2019. Hybrid strategy for selecting compact set of clustering partitions. Journal of Applied Soft Computing.
  • Marcílio C. P. de Souto, Pablo A. Jaskowiak, and Ivan Costa. 2015. Impact of missing data imputation methods on gene expression clustering and classification. BMC Bioinformatics, 16(1):64.
  • Teresa B. Ludermir, Marcílio C. P. de Souto, and Wilson Rosa de Oliveira. 2009. On a hybrid weightless neural system. International Journal of Bio-Inspired Computation, 1(1/2):93–104, 2009.
  • Marcílio C. P. de Souto et al. 2008. Clustering cancer gene expression data: a comparative study. BMC Bioinformatics, 9.
  • Marcílio C. P. de Souto et al. 2008. Ranking and selecting clustering algorithms using a meta-learning approach. In IJCNN, pages 3729–3735.
  • Katti Faceli, André de Carvalho, and Marcílio C. P. de Souto. 2007. Multi-objective clustering ensemble. International Journal of Hybrid Intelligent Systems, 4(3):145–156.