Welcome

Welcome to Laboratory of Computer Science in Control and Management of the Department of Automatic Control and Robotics, AGH University of Science and Technology in Krakow.

If you need help in solving problems within our capabilities (projects, orders), please visit the offer.

If you want to develop your skills in the field of data analysis and IT applications in automation, we invite you to cooperation.

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Team
Head of the Laboratory
Prof Jerzy Baranowski

Team
Prof Edyta Kucharska
Phd Marta Kraszewska
PhD Katarzyna Grobler-Dębska
PhD Waldemar Bauer
PhD Nataliia Kashpruk
MSc Adrian Dudek
MSc Rafał Mularczyk
MSc Daniel Dworak
BSc Karolina Świerczek
BSc Aleksandra Spiecha

Research

Data analysis methods in automatics and manufacturing

This area covers very wide applications of data analysis in the issues of estimation, classification and prediction. Specific areas of application include, but are not limited to, process and device diagnostics, fault prediction, load prediction, phenomena prediction or condition-based maintenance. The methods used in the research are mainly based on Bayesian statistics and selected areas of machine learning.

In this field, work is carried out on data processing, construction of classifiers and detection of events in time series.

Manufacturing control and management systems

In this field, research is conducted in two main areas. The first is the development of ERP software in the field of data science. Extending the functionality of such systems with analytical and predictive tools gives the possibilities of wide applications and significant benefits. The second area is the optimal control of the production process. This issue is related to the problem of optimal control. We work on the development of effective computational methods to optimize real manufacturing problems that may include unexpected disturbances and non-deterministic faults.

Numerical methods in system control

Our teamwork on effective numerical methods addressed to the problem of implementing methods and control algorithms and signal processing on various hardware platforms. The issues of approximation and implementation in real-time of filters and regulators with characteristics of incomplete order systems are considered. We develop algorithms and design methods to provide increased control system robustness.

Offer

Data analysis, machine learning and optimization

In the era of access to large amounts of data, adequate data treatment and analysis are necessary. Modern statistical methods allow for effective inference and prediction based on available information. A wide range of works related to data processing of various types is offered. Research in this area is carried out by the Information Technology Laboratory in Control and Management, headed by professor  Jerzy Baranowski.

We propose::

  • data analysis for scientific research purposes,
  • statistical process diagnostics,
  • development of statistical models of processes various types,
  • pattern classification and recognition methods,
  • prediction methods based on time series analysis with the use of expert knowledge,
  • diagnostic and prediction of faults,
  • optimization and control of discrete processes, in particular manufacturing.

Application:

The issues under consideration are fully within the scope of Industry 4.0, offering extensive support for many issues of modern production. The proposed works also apply in the areas of research, development and implementation of new products or installations.

Cooperation

The Information Technology Laboratory in Control and Management is looking for people willing to cooperate in the field of scientific research, implementation of scientific-covered projects and educational work.

Preferred skills and experience:

  • graduates in automation and robotics, computer science, mathematics or related fields,
  • knowledge of mathematics applications (such as numerical methods, statistics, optimization)
  • willingness to develop in directions such as:
    • data science (statistics, machine learning, data mining),
    • data analysis in management
    • process diagnostics,
    • modelling and optimization of industrial processes,
  • willingness to participate in research and development projects and industrial orders,
  • good knowledge of the English language,
  • knowledge of environments such as Python, Matlab, R, PostgreSQL, MySQL will be an additional advantage.

Terms of cooperation to be agreed (contact jb (at) agh.edu.pl)