Professor Eibe Frank

Professor (Computer Science)

Qualifications: Dipl-Inf Karlsruhe PhD Waikato

Contact Details

Room: G.2.18
Phone: +64 7 838 4396
Extension: 4396
Fax: +64 7 858 5095

Research Interests

Associate Professor Frank is a computer scientist whose primary area of interest is machine learning and its applications. He is a core developer of the WEKA machine learning software and has more than 100 publications on machine learning methods and applications of such methods to data mining, text mining, and areas of research outside computer science to his name.

Recent Publications

  • Muraoka, K., Hanson, P., Frank, E., Jiang, M., Chiu, K., & Hamilton, D. (2018). A data mining approach to evaluate suitability of dissolved oxygen sensor observations for lake metabolism analysis. Limnology and Oceanography: Methods, Early View, 15 pages. doi:10.1002/lom3.10283 Open Access version:

  • Vetrova, V., Coup, S., Frank, E., & Cree, M. J. (2018). Difference in details: transfer learning case study of cryptic plants and moths. In The Fifth Workshop on Fine-Grained Visual Categorization held in conjunction with CVPR 2018. Conference Website. Open Access version:

  • Gurulian, I., Markantonakis, K., Frank, E., & Akram, R. N. (2018). Good vibrations: artificial ambience-based relay attack detection. In Proc 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE) (pp. 481-489). Los Alamitos, California: IEEE Computer Society. doi:10.1109/TrustCom/BigDataSE.2018.00075

  • Bravo Marquez, F., Frank, E., & Pfahringer, B. (2018). Transferring sentiment knowledge between words and tweets. Web Intelligence and Agent Systems: an international journal, 19 pages. Retrieved from Open Access version:

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