Professor Albert Bifet

Albert Bifet

Professor (Computer Science)

Qualifications: PhD UPC

Personal Website:

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

  • Lobo, J. L., Oregi, I., Bifet, A., & Del Ser, J. (2020). Exploiting the stimuli encoding scheme of evolving Spiking Neural Networks for stream learning. Neural Networks, 123, 118-133. doi:10.1016/j.neunet.2019.11.021

  • 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

  • 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

Find more research publications by Albert Bifet


Data mining; Machine Learning

Contact Details

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