His research interest includes developing and optimizing multi-modality imaging techniques to better understand pathophysiology in early disease progression and to enhance the efficiency and efficacy of current diagnostic imaging. He combines deep learning and computer vision methods with advanced Ultrasound, MRI data acquisition and signal processing techniques to generate rapid, quantitative, and morphological magnetic resonance imaging (MRI) examinations.
He also advises and consults for several companies on a range of topics, including deep learning, US, MR imaging protocols, and data management, among others.