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Our team

The Data Science and Mining (DaSciM) team is part of the Computer Science Laboratory (LIX) of École Polytechnique, and the successor and evolution of the Data and Web Mining team (AUEB, Greece). In the previous years we have researched in the areas of databases and data mining. More specifically in unsupervised learning (clustering algorithms and validity measures), advanced data management and indexing (P2P systems, distributed indexing, distributed dimensionality reduction), text mining (word disambiguation for classification) and ranking algorithms (temporal extensions to PageRank).
More recently, supported by the DIGITEO Chair Levetone grant, we are working in large scale graph mining (degeneracy based community detection and evaluation), text mining and retrieval for web advertising/marketing and recommendations.The leader of the team has supervised previously nine completed Ph.D. theses and supervises six more underway and has published chapters in books and encyclopedias, two international books and more than a hundred twenty (120) papers in international refereed journals and conferences. Also we have coauthored three patents and attracted significant R&D funding including national and international research & development projects. Members of our team have received the ERCIM, Marie Curie, and Google fellowships.

Our team has co-organized the ECML PKDD 2011 conference in Athens. Members of the team participate in the editorial board of the Intelligent Data Analysis Journal and served as guest editors for special issues of the “Machine Learning” and “Data Mining & Knowledge Discovery” journals. Also co-chaired the PC committee of ECML/PKDD 2011 conference, served the Data Mining Track chair of the IEEE – ICDE 2011 conference and has participated as a conference committee member for more than fifty international conferences, in the areas: Databases, Data mining, Machine learning and the Web.
Moreover have a long experience in real-world industrial level software projects in the area of Large Scale Data/Text Mining. Currently we maintain collaborations with large industrial partners working on data science for Big Data projects including structured data, text and graphs. The director of the team has been invited and participated in three Google faculty EMEA summits in Zurich and London, in 2008, 2011 and 2012.

Also, check out our position paper entitled “Search in BigData2 – When Big Text meets Big Graph”, presented on the World Summit on Big Data and Organization Design, organized by IBM, Organizational Design Community, and the Interdisciplinary Center for Organizational Architecture/ Aarhus University, on May 16-17, 2013 in Paris.

Visit our selected publications page.


Team leader

Michalis Vazirgiannis
Professor

mvazirg ~ lix.polytechnique.fr
+33 (0)1 77578056
lix.polytechnique.fr/~mvazirg/

Dr. Vazirgiannis is a Professor in LIX, Ecole Polytechnique. He is currently working in the area of Data Science for Bigdata – aiming at harnessing the potential of machine learning algorithms for large scale data sets including text and graphs. More specifically his current work is on graph degeneracy for large scale graph mining, graph based text retrieval, learning models from time series data and text mining for the web (i.e. advertising, news streams).
He is involved in teaching in data mining and machine learning for big data in Ecole Polytechnique. He has supervised previously nine completed Ph.D. theses and supervises six more underway. He has published chapters in books and encyclopedias, two international books and more than a hundred twenty (120) papers in international refereed journals and conferences. He has received the ERCIM and Marie Curie EU fellowships. Also he has coauthored three patents and attracted significant R&D funding including national and international research & development projects. Currently he leads industrial projects in the area of large scale machine learning.

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