The COIN CoE develops methods for transforming the data produced by the current big data revolution into useful information. The key methodology for achieving this goal is statistical and computational inference based on the data. The emphasis is on large data collections and computationally demanding modelling and inference algorithms. Our mission is to push the boundary towards both more complex problems, requiring more structured data models, and towards extremely rapid inference. COIN brings in expertise on several different approaches to inference, with a unique opportunity to address the core computational challenges with combinations of machine learning, computational statistics, statistical physics, and constraint-based search and optimization. In addition to deep methodological work, we work on several applications in collaboration with selected top-level application partners from science and industry.

Contact person: Professor Petri Myllymäki
Home page: http://research.ics.tkk.fi/coin/

The COIN CoE is a joint effort by Aalto University and University of Helsinki, and is led by Professor Erkki Oja from Aalto university. The participating groups at University of Helsinki are the Complex Systems Computation (CoSCo) group at the Department of Computer Science and HIIT, the Bayesian Statistics group at HIIT and the Department of Mathematics and Statistics, and the Statistical Machine Learning and Bioinformatics group at HIIT.