The department was created in middle of sixties of the past century. Control applications based on physical modeling reached soon barrier that stems from complexity of the constructed models and impossibility to find feasible controllers to them. It was found that simple black-box models are often sufficient for design of efficient controllers. The need to learn model structure and its parameters stimulated interest in so called experimental identification. Search for an adequate methodology gradually singled out Bayesian methodology as the only known systematic tools suitable for solving the addressed class of problems. Gradually, following the improvements of the theoretical, algorithmic and evaluation tools, the interests have shifted to multivariate, non-linear and non-Gaussian cases. Also, control of basic level of technological processes has been gradually substituted by  higher level control and other application domains (physics, medicine, economy, societal decision making etc.). Attempt to created applicable generic tools and struggle with curse of dimensionality has become the main driving forces of the research we perform.