Dr Heitor Murilo Gomes

Senior Research Fellow (Computer Science)

Qualifications: BSc UTP MSc PhD PUCPR

Contact Details

Room: FG.2.03
Phone: +64 7 838 4104

About Heitor Murilo

Since his undergraduate studies, Heitor focuses his research in machine learning and data mining. This has not changed since, but now he focuses mainly on machine learning for data streams.

Research Interests

Data stream mining, ensemble methods, semi-supervised learning, feature selection.

Recent Publications

  • Barddal, J. P., Enembreck, F., Gomes, H. M., Bifet, A., & Pfahringer, B. (2019). Merit-guided dynamic feature selection filter for data streams. Expert Systems with Applications, 116, 227-242. doi:10.1016/j.eswa.2018.09.031

  • Gomes, H. M., Mello, R. F. D., Pfahringer, B., & Bifet, A. (2019). Feature Scoring using Tree-Based Ensembles for Evolving Data Streams. In Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019 (pp. 761-769). doi:10.1109/BigData47090.2019.9006366

  • Grzenda, M., Gomes, H. M., & Bifet, A. (2019). Delayed labelling evaluation for data streams. Data Mining and Knowledge Discovery. doi:10.1007/s10618-019-00654-y

  • Gomes, H. M., Bifet, A., Fournier-Viger, P., Granatyr, J., & Read, J. (2019). Network of experts: Learning from evolving data streams through network-based ensembles. In Proc International Conference on Neural Information Processing (ICONIP 2019) LNCS 11953 (pp. 704-716). Sydney, Australia: Springer. doi:10.1007/978-3-030-36708-4_58

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