What is your doctoral research about?
In my research, I focus on Explainable AI techniques. I think they're crucial not just for better understanding of Machine Learning but also for discovering unknown relationships which can be further investigated. Additionally, I evaluate existing Explainable AI algorithms to ensure their accuracy and identify areas for improvement. My specific areas of interest include medicine, manufacturing, and Olfactometry.
How can AI and especially Explainable AI be of help in the field of medicine?
In my view, AI is a powerful tool to be implemented in Decision Support Systems. It helps medical personnel in identifying higher-risk patients earlier and more efficiently. The deployment of Explainable AI allows them to analyze model predictions, especially when there is a disagreement with their knowledge, helping them make informed decisions on whether to trust the AI in a given case.
Doctoral students recently attended a retreat in Poznań as part of the Research School. What did you do at the retreat?
This year, I co-organized the "Systems" Cluster meeting in Poznań, Poland, where we aimed to increase collaboration among research groups and discuss the cluster's structure. In my view, we reached several interesting conclusions during the symposium. On the last day, we had a guided tour to Gniezno, the first Polish capital, exploring historical buildings dating back to the 10th century. I thoroughly enjoyed this year's Fall Retreat and look forward to similar experiences in the future, perhaps even exploring the countries of our colleagues in the upcoming years.
