Albert Bifet is a big data scientist with 10+ years of international experience in research and in leading new open source software projects for business analytics, data mining, and machine learning (Huawei, Yahoo, University of Waikato, UPC). He obtained a Ph.D. from UPC-BarcelonaTech. Albert has worked in Hong Kong, New Zealand, and Europe. At Yahoo Labs, he co-founded Apache SAMOA (Scalable Advanced Massive Online Analysis) in 2013. Apache SAMOA is a distributed streaming machine learning (ML) framework that contains a programing abstraction for distributed streaming ML algorithms. At the WEKA Machine Learning group, he has co-led MOA (Massive Online Analysis) since 2008. MOA is the most popular open source framework for data stream mining, with more than 20,000 downloads each year. Albert is the author of the book Adaptive Stream Mining: Pattern Learning and Mining from Evolving Data Streams. Additionally, he was editor of the Big Data Mining special issue of SIGKDD Explorations in 2012. Also, he is serving as co-chair of the Industrial track of ECML PKDD 2015, and served as co-chair of BigMine (2017-2012), and ACM SAC Data Streams Track (2018-2012).
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