With Prof. Sokolovsky we use Machine Learning and other computational analysis methods to enhance asthma diagnosis in children. We analyze respiratory sounds and data related to genetic markers and phenotypic traits, creating a computer-aided diagnostic model. This model helps understand how these factors interact, allowing for improved diagnosis accuracy.

Our research with Prof. Furman is more experimental, utilizing nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI) techniques to study the microstructure of neuronal and collagenous tissues. We are developing models and examining relaxation mechanisms in these tissues, verifying our results with actual samples. We aim to create new MRI methods to better understand these structures. Additionally, we're developing an imaging contrast method for tissues, aiming to create clearer, more informative images.