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). Boosting decision stumps for dynamic feature selection on data streams. Information Systems, 83, 13-29. doi:10.1016/ Open Access version:

  • Gomes, H. M., Bifet, A., Read, J., Barddal, J. P., Enembreck, F., Pfahringer, B., . . . Abdessalem, T. (2019). Correction to: Adaptive random forests for evolving data stream classification (Machine Learning, (2017), 106, 9-10, (1469-1495), 10.1007/s10994-017-5642-8). Machine Learning. doi:10.1007/s10994-019-05793-3

  • 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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11953 LNCS (pp. 704-716). doi:10.1007/978-3-030-36708-4_58

  • 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

Find more research publications by Heitor Murilo Gomes