Data-Centric Systems Engineering

The aim of our research lab is to explore how emerging artificial intelligence solutions can most effectively support companies and industry to operate efficiently. In other words, we are interested in how we can most effectively support process improvement, optimal and safe operation, and fault detection using the vast amount of data available in industry.

We are also interested in the development of fully autonomous systems, where the system has to adapt continuously to a changing and uncertain environment. So, our main research areas, but not limited to, are the following:

• Machine learning applications from the data collection to the deployment and model maintanance

• Development of hybrid models (integrate machine learning models with first principle models)

• Advanced process monitoring

• Advanced Process Control

• Process Optimization and Intensification

• Real-time adaptive learning and agile decision making

• Design of experiments

• Stochastic modeling and optimization

• Deep learning

  • Feed Forward-, Convolutional- and Recurrent Neural Networks

  • Physics Informed Neural Networks

  • Generative Adversarial Networks

  • Graph Neural Networks

• Reinforcement Learning for solving complex problems (process design, optimization, control, decision support, etc...)

If you are interested in our work, please contact me!

e-mail: kummer.alex@mk.uni-pannon.hu