I am Associate Professor in Big Data at LTCI, Telecom ParisTech, University Paris Saclay. My research focuses on Data Stream mining, Big Data Machine Learning and Artificial Intelligence. Problems I investigate are motivated by large scale data, the Internet of Things (IoT), and Big Data Science.
I am also co-leading the open source projects MOA Massive On-line Analysis and Apache SAMOA Scalable Advanced Massive Online Analysis.
- ACM Distinguished Speaker
- Invited Keynote Speaker KDD Workshop on Mining and Learning from Time Series (MiLeTS 2017)
- Invited Speaker The 8th Asian Conference on Machine Learning (ACML 2016)
- Invited Speaker The 16th International Conference on Artificial Intelligence and Soft Computing ICAISC 2017
- Tutorial on IoT in Practice: Case Studies in Data Analytics, with Issues in Privacy and Security. Held at KDD 2017 (August 13, Halifax, Canada)
- Hands-on Tutorial on Massive Online Analytics. Held at KDD 2017 (August 15, Halifax, Canada)
- KDD BigMine 2017. A forum bringing together researchers exploring all aspects of Big Data and IoT Analytics. Held at KDD 2017 (August 14, Halifax, Canada)
- Albert Bifet, Jiajin Zhang, Wei Fan, Cheng He, Jianfeng Zhang, Jianfeng Qian, Geoff Holmes, Bernhard Pfahringer: Extremely Fast Decision Tree Mining for Evolving Data Streams. KDD 2017: 1733-1742
- Albert Bifet: Classifier Concept Drift Detection and the Illusion of Progress. ICAISC (2) 2017: 715-725
- Heitor Murilo Gomes, Albert Bifet, Jesse Read, Jean Paul Barddal, Fabrício Enembreck, Bernhard Pfharinger, Geoff Holmes, Talel Abdessalem: Adaptive random forests for evolving data stream classiﬁcation. Machine Learning, Springer, 2017.
- Heitor Murilo Gomes, Jean Paul Barddal, Fabrício Enembreck, and Albert Bifet: A Survey on Ensemble Learning for Data Stream Classification. ACM Comput. Surv. 50, 2, Article 23 (March 2017), 36 pages.
- Diego Marron, Jesse Read, Albert Bifet, Nacho Navarro: Data stream classification using random feature functions and novel method combinations. Journal of Systems and Software 127: 195-204 (2017)