Arif Khan is a leading researcher in computational imaging, focusing on the critical role medical images play in the diagnosis and monitoring of diseases, as well as in the planning and guidance of surgical therapies. His group develops and applies sophisticated image processing and analysis techniques to extract, quantify, and distill information from medical images, ultimately aiming for accurate diagnoses and precise surgical interventions. Research interests include image-guided neurosurgery for treating drug-resistant epilepsy and brain cancer, where they create computational tools to guide neurosurgeons in optimal resections and biopsies. Additionally, they focus on the intersection of histology and imaging, developing semi-automated pipelines for image registration and exploring correlations between imaging and histological markers. Khan's multidisciplinary research also investigates alterations in brain structure related to neurological disorders, using both anatomical and diffusion MRI techniques. A strong emphasis is placed on developing novel computational tools to enhance medical imaging analysis, with applications spanning various domains in clinical neuroscience.