Contact Details

Email: abifet@waikato.ac.nz
Room: FG.2.02
Phone: +64 7 838 4704
Extension: 4704
Website: http://albertbifet.com/

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: https://ai.waikato.ac.nz/

Recent Publications

• del Campo-Ávila, J., Takilalte, A., Bifet, A., & Mora-López, L. (2020). Binding data mining and expert knowledge for one-day-ahead prediction of hourly global solar radiation. Expert Systems with Applications. doi:10.1016/j.eswa.2020.114147

• Bahri, M., Pfahringer, B., Bifet, A., & Maniu, S. (2020). Efficient batch-incremental classification using UMAP for evolving data streams. In M. R. Berthold, A. Feelders, & G. Krempl (Eds.), Proc Advances in Intelligent Data Analysis IVIII: 18th Symposium on Intelligent Data Analysis (IDA 2020) Vol. LNCS 12080 (pp. 40-53). Konstanz, Germany: Springer. doi:10.1007/978-3-030-44584-3_4

• Cerqueira, V., Gomes, H. M., & Bifet, A. (2020). Unsupervised concept drift detection using a student–teacher approach. In A. Appice, G. Tsoumakas, Y. Manolopoulos, & S. Matwin (Eds.), Proc 23rd International Conference on Discovery Science (DS 2020) Vol. LNAI 12323 (pp. 190-204). Thessaloniki, Greece: Springer. doi:10.1007/978-3-030-61527-7_13

• Bifet, A., Carvalho, A., Ferreira, C., & Gama, J. (2020). Editorial message: Special track on data streams. In Proceedings of the ACM Symposium on Applied Computing (pp. 481). doi:10.1145/3389651

Find more research publications by Albert Bifet