About the Laboratory

The research activities of the laboratory focus on the application of evolutionary computing procedures, stochastic optimization, machine learning, and visualization procedures. In addition, the laboratory's activities are directed towards researching efficient algorithms, developing new optimization methods, applying optimization and machine learning in real-life situations, and integrating these technologies to solve complex problems.

The members of the laboratory have conducted comprehensive research in the field of scheduling, within research projects or industry collaboration projects. Solving scheduling problems is based on the integration of evolutionary computing procedures and machine learning procedures, applying the principles of hyperheuristics to develop customized scheduling procedures. This approach proves successful in diverse domains, such as manufacturing processes, vehicle routing, or solving logistics problems in warehouses.

Another important area of activity is the development of customized optimization procedures in the field of computer security and cryptography, primarily for the development of enhanced cryptographic primitives with non-trivial constraints and multiple criteria. Recently, the field of artificial intelligence security is actively studied with the aim of developing robust models that are more resistant to malicious instances and various attacks, such as side-channel attacks. Also, the development of customized optimization procedures yields effective results in the automated detection of software errors and vulnerabilities, which can have a significant impact given the current speed of application development.