Albert BIFET

Institut Polytechnique – Paris, France

& University of Waikato- Hamilton, New Zealand

 Albert Bifet is Professor at University of Waikato and IP Paris. Previously he worked at Huawei Noah's Ark Lab in Hong Kong, Yahoo Labs in Barcelona, and UPC BarcelonaTech. He is the co-author of a book on Machine Learning from Data Streams published at MIT Press. He is one of the leaders of MOA, scikit-multiflow and Apache SAMOA software environments for implementing algorithms and running experiments for online learning from evolving data streams. He is a member of the Steering Committee of ECML-PKDD.

Pascal CUXAC

INIST - CNRS, France

Pascal Cuxac is Research Engineer at the INIST/CNRS (Institute for Scientific & Technical Information / National Center for Scientific Research) in Nancy, France. He obtained his PhD in Geological and Mining Engineering from the National School of Geology in 1991 and he was working on mechanical behavior of anisotropic rock. In 1993, he joined the CNRS as Research Engineer. Currently, in INIST Research & Development Department, he takes part in a research program on classification methods applied to bibliographic corpora, in particular in the development of an incremental unsupervised clustering algorithm. Up to now, he is the INIST- Text & Data Mining team leader, working on the automatic disambiguation and alignment of geographical named entities. He is member of the program committee of major international conferences (IJCNN-International Joint Conference on Neural Networks; IEEE CIS-Computational Intelligence Society; IEA/AIE-Industrial, Engineering and Other Applications of Applied Intelligent Systems; ISKO-Maghreb; IMMM-International Conference on Advances in Information Mining and Management...). He is the author or co-author of a book chapter and more than 71 articles in journals and international conferences. 7 of his publications received awards for best papers

Jean-Charles LAMIREL

 LORIA - INRIA, France

Jean-Charles Lamirel is Lecturer since 1997. He obtained his PhD in Computer Science in 1995 and his Research Accreditation in the same domain in 2010. He is currently teaching Information Science at the University of Strasbourg (France), Machine Leaning as invited Sea-Sky Professor at University of Dalian (China) and achieving his research at the INRIA laboratory of Nancy. He was a research member of the INRIA-CORTEX project whose scope is Neural Networks and Biological Systems. He has recently integrated the INRIA-TALARIS project whose main concern is automatic language and text processing. Jean-Charles Lamirel main domains of research are textual data mining based on neural networks, multiple viewpoints data analysis paradigms, data mining auto-evaluation methods and evolving data mining. He is the main author of more than 150 international contributions, board member of the international Webometrics journal: "Collnet Journal of Scientometrics and Information Management" and takes part in the committees of ICDM, ICTAI, IJCNN main conferences. He is in the steering committee of the Kohonen’s WSOM conference series and was the main organizer of the last WSOM 2017 edition. He is also chief editor of special issues of international journals like NCAA and member of the IEEE task force on "Evaluation and quality issues in data mining" within the Data Mining Technical Committee (committee member of the corresponding PAKDD-QIMIE workshops). 

Manuel ROVERI

Department of Electronics and Information – Politecnico di Milano, Italy

Manuel Roveri received the Dr. Eng. degree in Computer Science Engineering from the Politecnico di Milano (Italy) in June 2003, the MS in Computer Science from the University of Illinois at Chicago (USA) in December 2003 and the Ph.D. degree in Computer Engineering from the Politecnico di Milano (Italy) in May 2007. He has been Visiting Researcher at Imperial College London (UK) in 2011. Currently, he is an Associate Professor at the Department of Electronics and Information of the Politecnico di Milano (Italy). Current research activity addresses Embedded and Edge Artificial Intelligence, Tiny Machine and Deep Learning, and Learning in nonstationary/evolving environments. Manuel Roveri is a Senior Member of IEEE and served as Chair and Member in several IEEE Committees. He holds 1 patent and has published about 100 papers in international journals and conference proceedings He is the recipient of the 2018 IEEE Computational Intelligence Magazine “Outstanding Paper Award” and of the 2016 IEEE Computational Intelligence Society “Outstanding Transactions on Neural Networks and Learning Systems Paper Award”.