Albert Bifet is a professor at LTCI and head of the Data, Intelligence, and Graphs (DIG) Group at Télécom ParisTech, and a scientific collaborator at École Polytechnique. A big data scientist with 10+ years of international experience in research, Bifet has led new open source software projects for business analytics, data mining, and machine learning at Huawei, Yahoo, the University of Waikato, and UPC.
At Yahoo Labs, he co-founded Apache SAMOA (Scalable Advanced Massive Online Analysis), a distributed streaming machine learning framework that contains a programming abstraction for distributed streaming ML algorithms. At the WEKA Machine Learning Group, he co-led MOA (Massive Online Analysis), the most popular open source framework for data stream mining, with more than 20,000 downloads each year.
Bifet is the author of "Adaptive Stream Mining: Pattern Learning and Mining from Evolving Data Streams," co-author of "Machine Learning for Data Streams," and the editor of the "Big Data Mining" special issue of SIGKDD Explorations in 2012. He was co-chair of the industrial track at ECML PKDD 2015, BigMine (2014, 2013, 2012), and the data streams track at ACM SAC (2015, 2014, 2013, 2012). He holds a PhD from BarcelonaTech.
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