Professor Albert Bifet
Te Ipu o te Mahara AI Institute Director
Qualifications: PhD UPC
Albert is a Professor of AI, Director of the Te Ipu o te Mahara AI Institute at the University of Waikato and Co-chair of the Artificial Intelligence Researchers Association (AIRA). His research focuses on Artificial Intelligence, Big Data Science, and Machine Learning for Data Streams.
He is leading the TAIAO Environmental Data Science project, and he is co-leading the open source projects MOA Massive On-line Analysis, StreamDM for Spark Streaming and SAMOA Scalable Advanced Massive Online Analysis.
He is the co-author of a book on Machine Learning from Data Streams published at MIT Press. He served as PC Co-Chair of DSAA'2021, Co-Chair of the Industrial track of IEEE MDM 2016, ECML PKDD 2015, and as Co-Chair of KDD BigMine (2019-2012), and ACM SAC Data Streams Track (2023-2012).
Te Ipu o te Mahara AI Institute: https://ai.waikato.ac.nz/
Petri, I., Chirila, I., Gomes, H., Bifet, A., & Rana, O. (2022). Resource-Aware Edge-Based Stream Analytics. IEEE Internet Computing. doi:10.1109/MIC.2022.3152478
Cerqueira, V., Gomes, H. M., Bifet, A., & Torgo, L. (2022). STUDD: a student–teacher method for unsupervised concept drift detection. Machine Learning. doi:10.1007/s10994-022-06188-7
Mordvanyuk, N., López, B., & Bifet, A. (2022). TA4L: Efficient temporal abstraction of multivariate time series. Knowledge-Based Systems, 244. doi:10.1016/j.knosys.2022.108554
Bifet, A., Ferreira, C., Gama, J., & Gomes, H. M. (2022). EDITORIAL MESSAGE Special Track on Data Streams. In Proceedings of the ACM Symposium on Applied Computing (pp. 449). doi:10.1145/3535426
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