AI for biomedical image analysis and its application areas in computational oncology, neurological disorders and biomarker discovery. Analysis of complex, non-linear and high-dimensional biomolecular data (spatial Omics). Multi-modal multi-scale biomedical data integration to bridge the current gap between molecular and anatomical phenotypes.
My developments enable data integration from the molecular level (mass spectrometry imaging) to cell level (imaging microscopy) up-to the organ level (magnetic resonance imaging). We use these developments to address key questions for drug distribution in brain tumor of glioblastoma, and identification of 2D/3D biomolecular patterns that are expected to provide deep insights about molecular mechanisms in some complex diseases such as neurological disorders and tumor heterogeneity.