Mathews Jacob

Mathews Jacob is a Professor of Electrical and Computer Engineering at the University of Virginia’s School of Engineering and Applied Science, leading the Computational Biomedical Imaging Group (CBIG). His research focuses on image reconstruction, analysis, and quantification in MRI, particularly in ultrahigh-resolution brain MRI, cardiac/pulmonary MRI, and metabolic imaging. He holds a B.Tech from National Institute of Technology, M.E. from Indian Institute of Science, and Ph.D. from Swiss Federal Institute of Technology.

Research Contributions: Dr. Jacob pioneered model-based deep learning frameworks like MoDL and MOL, advancing accelerated MRI techniques. His work bridges machine learning and medical imaging, with applications in dynamic speech MRI, motion-compensated cardiac imaging, and compressed sensing.

Professional Roles: He serves as Associate Editor for IEEE Transactions on Medical Imaging and was General Chair of IEEE International Symposium on Biomedical Imaging (2020). A Fellow of IEEE (2022), he has received NSF CAREER (2009), ACS Research Scholar (2011), and Eminent Researcher (2024) awards.

Grants & Projects: His NIH-funded projects include ultra-high-resolution multi-contrast MRI, free-breathing dynamic MRI, and MR spectroscopic imaging for Alzheimer’s research. Current grants emphasize computational MRI innovations.

Labs & Impact: The CBIG lab develops cutting-edge imaging algorithms, collaborating on clinical applications like pulmonary hypertension detection via cardiac MRI radiomics. His work impacts radiology, oncology, and neurology.