More recently, 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 twelve completed Ph.D. theses 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 co-authored three patents and attracted significant R&D funding including national and international governmental/industrial sources. 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 our group has 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.
Professor Vazirgiannis leads the X/AXA Data Science Chair.
- 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.
- the ERCIM White Paper on Big Data Analytics here.
Another relevant research topic is decision making methods, in particular: mathematical programming (mixed integer linear and nonlinear programming), combinatorial optimization, global optimization, graph theory. We are interested both in methodology and applications, with a special focus on applications in energy optimization and computational geometry.
Visit our selected publications page.
mvazirg ~ lix.polytechnique.fr
+33 (0)1 77578056
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 data mining & machine learning.