This research group aims to make research results applicable in the field of collecting and data storage, their analysis by using complex procedures of computer intelligence and machine learning (for the web, mobile and service environments and real-time data analysis) as well as parallel and distributed data processing in energy efficient high-performance computer systems.
There are possibilities for professional cooperation with respect to an efficient application of cloud computing, automated testing and setting in motion multiple platform web, mobile and embedded software solutions based on the current methodologies and platforms including agile development procedures, test-driven development and open-source environment. Those solutions include the procedures of detecting, collecting and data processing from scientific and embedded systems as well as the Internet of Things. Cooperation can be realized within the application and adjustment of machine learning procedures for the purposes of pattern recognition (classification, regression, etc.) and cognitive procedures applied to various problems and data. Since optimisation problems range from machine learning modelling to building solar panels in fields, development, adjustment and embedding of different evolutionary algorithms can be used to tackle the problems. For time critical services, the data-flow real-time analysis, business intelligence approaches and appropriate visualisations are used. The main fields of application are biomedicine and medical services, mobility and transportation system, agriculture, food industry, smart and energy efficient environment, scientific computing, cybersecurity, business computer systems and data centres of companies and institutions.
