Doctoral Study
Explainable Artificial Intelligence (XAI)
🧬 Research Focus
Currently, I focus on the field of Explainable AI (XAI). The goal of my research is to find and develop methods that allow explaining the decision-making process of complex "black-box" machine learning models, especially deep neural networks.
Transparency and interpretability are crucial for deploying AI in critical domains such as medicine or finance.
🧪 Current Status
- Phase
Literature review and formulation of research questions.
- Methods
Analysis of existing XAI techniques (SHAP, LIME, Attention weights).
- Note
Publications and research results will be gradually added to this page.