I have more than 15 years experience in computer vision, signal processing, graph theory, medical imaging and informatics. I have had continuous and successive experiences in forming and leading research teams comprising of basic and clinical scientists in executing NIH-funded research projects. I have published more than 70 peer reviewed papers ranging from microwave engineering, superconductivity, image/signal processing, vision, graph theory and neuroscience, and two US patents. I have attracted several NIH grants, on graph algorithms for accelerated MRI, theoretical neuroscience and network modeling of dementia and Parkinson’s.

The defining characteristic of my work has been inter-disciplinarity: finding innovative ways to apply computation and algorithms to biomedical applications. My group was an early adopter of mathematical models of brain connectivity networks, a subject that marries computer science with neuroradiology. I have deep interest in the graph properties of brain networks, and how they are altered in neurological disorders like epilepsy, dementia, movement disorders, traumatic brain injury and stroke. A recent project on dementia modeling was selected by the NIH for the prestigious EUREKA award that supports highly innovative but risky research, and another by the BRAIN Initiative. My team has developed novel image reconstruction algorithms for fast MRI, motion correction for MR angiography, and new methods in tractography, Q-ball imaging, brain connectivity networks and computational neurology.

My research program is now perfectly poised to help bring the fields of neurology and radiology into the era of personalized, precision medicine, using mathematical modeling and data science.