The rapid advancements in artificial intelligence (AI) have transformed brain cancer research, offering unprecedented capabilities in diagnostics, treatment planning, and predictive analytics. This keynote presentation will explore the role of AI in addressing critical challenges in neuro-oncology, such as the accurate classification of tumor types and grades, automated segmentation of tumor regions in MRI scans, and the prediction of patient survival outcomes. The keynote will discuss innovative applications, including explainable AI (XAI) techniques that enhance the transparency of AI models, fostering trust and facilitating their adoption in clinical settings. The integration of multimodal data—combining medical images and patient demographics—will be highlighted as a pathway to more robust and personalized care. The emerging concept of digital twins in neuro-oncology will be discussed, illustrating how AI-powered virtual models can simulate individual patient scenarios to optimize care and predict disease progression in the context of precision medicine.

Robertas Damaševičius is a professor at the Department of Software Engineering at Kaunas University of Technology and at the Department of Applied Informatics at Vytautas Magnus University, Lithuania, and an adjunct at the Faculty of Applied Mathematics, Silesian University of Technology, Poland. With extensive expertise in artificial intelligence, medical imaging, and digital health, he is a recognized thought leader in his fields. Prof. Damaševičius has a strong background in doctoral supervision and project evaluation, serving as an editor and associate editor for numerous international journals such as Information Technology and Control, and International Journal of Imaging Systems and Technology (IMA). He has delivered keynote speeches at prestigious conferences worldwide, sharing his insights on topics ranging from AI in product development to sustainable health systems and digital twins. His recent research interests include explainable AI, computational intelligence, and digital health twins. He has authored over 400 publications, which have been cited more than 21,000 times. His h-index of 77 reflects the reach and impact of his contributions to the field. Beyond academia, he actively collaborates on international projects and engages in knowledge transfer initiatives to bridge the gap between research, education and practical applications.