The Data Science and Mining (DaSciM) team is part of the Computer Science Laboratory (LIX) of École Polytechnique. In the previous years we have conducted research in the areas of databases and data mining. More specifically in unsupervised learning, advanced data management and indexing, text mining and ranking algorithms.
More recently, we are working in large scale graph mining, text mining and retrieval for web advertising/marketing and recommendations. As well as on applications to bioinformatics via graph kernels for graph similarity. But also in Big Data analytics with time series databases handling for financial data, Multi-attribute time series for indexing/quering.
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.
Another relevant research topic is decision making methods, in particular: mathematical 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.
Ioannis Nikolentzos (Polytechnique)
Martina Cerulli (Cnrs)
Gabriele Iommazzo (Polytechnique)
Stratis LIMNIOS (Polytechnique)
George Panagopoulos (Polytechnique)
Jean-Baptiste REMY (Polytechnique)
Changmin WU (Polytechnique)