Computationally Efficient Methods for
Deep Computing (DeepC)

A research project in the research programme on
Mathematical Methods and Modeling in the Sciences (MaDaMe),
funded by Academy of Finland and Helsinki Institute for Information Technology (HIIT).


Deep Computing is a term for methods solving complex and large-scale modeling and analysis problems with emerging computer systems that combine ultrafast processing with sophisticated analytical software. Deep Computing can be seen to consist of three intertwined research areas:

The DeepC project has two major objectives:

A prototype mobile user location system, developed by the CoSCo group. The location of a mobile terminal (red area) is inferred from a set of available signal strength measurements. An example of a 3D visualization of a high-dimensional data set, produced by a novel Bayesian visualization technique developed by the CoSCo group. In this particular example, each point in the picture represents a session path of a WWW site visitor, and the colors of the points correspond to different type of user profiles.

Some of the methods developed in the project have been implemented in the B-Course software, a unique Bayesian web-based interactive tutorial and data analysis service publicly available at address

Contact person

Professor Henry Tirri
Complex Systems Computation group (CoSCo)
Department of Computer Science
University of Helsinki, Finland