Professor Albert Bifet

Professor (Computer Science)

Qualifications: PhD UPC

Contact Details

Room: FG.2.02
Phone: +64 7 838 4704
Extension: 4704

About Albert

Albert is a computer scientist whose primary area of interest is Artificial Intelligence/Machine Learning for data streams and its applications. He is a core developer of the MOA machine learning software and has more than 120 publications on machine learning methods and their applications.

Waikato AI Initiative:

Recent Publications

  • Lobo, J. L., Del Ser, J., Bifet, A., & Kasabov, N. (2020). Spiking Neural Networks and online learning: An overview and perspectives. Neural Networks, 121, 88-100. doi:10.1016/j.neunet.2019.09.004

  • Chehreghani, M. H., Bifet, A., & Abdessalem, T. (2019). An in-depth comparison of group betweenness centrality estimation algorithms. In Proc 2018 IEEE International Conference on Big Data, Big Data 2018 (pp. 2104-2113). Seattle, WA, USA. doi:10.1109/BigData.2018.8622133

  • Montiel, J., Bifet, A., Losing, V., Read, J., & Abdessalem, T. (2019). Learning fast and slow: A unified batch/stream framework. In Proc 2018 IEEE International Conference on Big Data (Big Data 2018) (pp. 1065-1072). Seattle, WA, USA. doi:10.1109/BigData.2018.8622222

  • Bifet, A., Hammer, B., & Schleif, F. M. (2019). Recent trends in streaming data analysis, concept drift and analysis of dynamic data sets. In Proc 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2019) (pp. 421-430).

Find more research publications by Albert Bifet