Dr Krzysztof Gajowniczek became a scholarship holder of the Minister of Education and Science
Dr Krzysztof Gajowniczek works at the Department of Artificial Intelligence at the Institute of Information Technology.
His area of research focuses on the methods of machine learning and data mining within IT and telecommunications.
Artificial Intelligence in practice
The main subject of the research conducted by dr Krzysztof Gajowniczek is the creation, development and practical application of widely understood methods of artificial intelligence to build systems supporting decision-making processes in the economy and engineering.
When building such systems it is very important to understand the environmental conditions and the needs of the end user.
Incorporating the expert knowledge would not be possible without close, multi-stage interaction with researchers specializing in a given issue.
This interaction leads to the formation of a system with the required assets, and also to show the researchers specializing in very distant fields, the possibilities offered by modern information technologies.
The challenges of modern computational methods
The challenges faced by modern computational methods are as follows:
- The problem of the quality of the delivered results and the generalization of knowledge.
- The problem of the explainability of the solution. The algorithms provide solutions that can be understood by people, which contrasts with the so-called “Black box” concept, and even its designers sometimes cannot explain why the AI made a certain decision.
- The problem of the user-friendliness of the developed software, i.e. the whole experience that the user experiences when using the product, during human-computer interaction. All the above-mentioned challenges are the key inspiration for the developed calculation methods.
New computational methods
Considering the motivation of the conducted research and the challenges facing modern computational methods, the scope of the work is aimed at developing new methods that will be able to :
- improve the overall performance of predictive models,
- take into account domain knowledge,
- enable the explanation of dependencies occurring in the analyzed problem,
- support decision-making processes in business practice and engineering.
Links to the systems:
https://www.scopus.com/authid/detail.uri?authorId=56538513800
https://publons.com/researcher/1550125/krzysztof-gajowniczek
https://nauka-polska.pl/#/profile/scientist?id=277334&_k=dqq6r9
https://www.researchgate.net/profile/Krzysztof-Gajowniczek
https://scholar.google.pl/citations?user=UJpaHXgAAAAJ&hl=pl&oi=ao