AI/ML & Biomedical Imaging in Disease

I will talk about our recent research on new methodologies advancing the frontiers of AI/ML and computational imaging techniques (multimodal data registration, weakly supervised annotation, image quality enhancement, and eXplainable AI).

Bartek has established an independent research group that focuses on medical imaging and machine learning at Big Data Institute. He is proud to have initiated several new, multidisciplinary research projects that integrate imaging and non-imaging modalities, driving the development of innovative image analysis and machine learning algorithms. Notably, his research projects encompass both the theoretical foundations of AI/ML algorithms (such as image quality, image segmentation, or image registration), and applied AI/ML for longitudinal disease monitoring (using imaging, patient records, and Natural Language Processing), identification of disease therapeutic targets (using imaging & genetic data integration), and more recently, multimodal cancer imaging & radiogenomics.

Bartek graduated in Electrical Engineering from the AGH University of Science and Technology in Kraków (Poland) in 2009. He completed a PhD at the University of Central Lancashire (UK) in 2012.