Albert Bifet is Full Professor at the University of Waikato in New Zealand and LTCI, Telecom Paris, IP-Paris. Previously he worked at Huawei Noah’s Ark Lab in Hong Kong, Yahoo Labs in Barcelona, University of Waikato and UPC BarcelonaTech.
Bifet is the co-author of a book on Machine Learning for Data Streams at MIT Press, and author of a book on Adaptive Stream Mining and Pattern Learning and Mining from Evolving Data Streams. He is one of the leaders of MOA, scikit-multiflow, Apache SAMOA and streamDM software environments for implementing algorithms and running experiments for online learning from evolving datastreams. He has served as Co-chair of the Industrial Track of IEEE MDM 2016, ECML PKDD 2015, KDD BigMine (2019-2012), and Data Streams Track of the ACM/SIGAPP Symposium on Applied Computing (SAC 2020-2021).
