Professor Bernhard Pfahringer

Professor (Computer Science)

Qualifications: MEng PhD Vienna Tech

Contact Details

Room: G.1.24
Phone: +64 7 838 4041
Extension: 4041

About Bernhard

Find out more about Bernhard and his work by viewing his professorial lecture: Dawn of the Age of Data: a Lecture to look at the data revolution (October 2015).

Research Interests

Data mining, machine learning, heuristic optimisation, programming languages.

Teaching Commitments

Recent Publications

  • Bravo-Marquez, F., Frank, E., Pfahringer, B., & Mohammad, S. M. (2019). AffectiveTweets: a Weka package for analyzing affect in tweets. Journal of Machine Learning Research, 20, 1-6. Retrieved from 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

  • Sahito, A., Frank, E., & Pfahringer, B. (2019). Semi-supervised learning using Siamese networks. In J. Liu, & J. Bailey (Eds.), Proc 32nd Australasian Joint Conference on Advances in Artificial Intelligence (AI 2019), LNCS 11919 (pp. 586-597). Cham: Springer. doi:10.1007/978-3-030-35288-2_47

  • Leathart, T., Frank, E., Pfahringer, B., & Holmes, G. (2019). Ensembles of nested dichotomies with multiple subset evaluation. In Q. Yang, Z. -H. Zhou, Z. Gong, M. -L. Zhang, & S. -J. Huang (Eds.), Advances in Knowledge Discovery and Data Mining: Proc 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2019), LNCS 11439 Vol. Part I (pp. 81-93). Cham: Springer. doi:10.1007/978-3-030-16148-4_7

Find more research publications by Bernhard Pfahringer