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

  • 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., 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, 108, 1877-1878. doi:10.1007/s10994-019-05793-3

  • Gomes, H. M., Read, J., & Bifet, A. (2019). Streaming random patches for evolving data stream classification. In Proceedings - IEEE International Conference on Data Mining, ICDM Vol. 2019-November (pp. 240-249). doi:10.1109/ICDM.2019.00034

  • 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:

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