Rate My Professor Mathews Jacob

Mathews Jacob is a Professor of Electrical and Computer Engineering in the School of Engineering and Applied Science at the University of Virginia, where he heads the Computational Biomedical Imaging Group (CBIG). He earned his PhD in Biomedical Imaging from the Swiss Federal Institute of Technology in 2003, MS in Signal Processing from the Indian Institute of Science in 1999, and BSE in Electrical and Communication Engineering from the National Institute of Technology in 1996. Before joining the University of Virginia, he served on the faculty at the University of Iowa, receiving the Faculty Excellence Award for Research in 2021 and Research Excellence Award in 2020. Earlier, he was a Beckman postdoctoral fellow at the University of Illinois at Urbana-Champaign.

Jacob's research focuses on machine learning algorithms for image reconstruction and inverse problems, particularly in magnetic resonance imaging (MRI), including ultrahigh resolution brain MRI, cardiac and pulmonary MRI, and metabolic imaging. His lab develops mathematical tools and applied algorithms for medical image reconstruction, analysis, and quantification, collaborating with clinical researchers in areas such as magnetic resonance imaging, near infrared spectroscopic imaging, and microscopy. Key publications include "MoDL: Model Based Deep Learning Architecture for Inverse Problems" (IEEE Transactions on Medical Imaging, 2019), "Local monotone operator learning using non-monotone operators: MnM-MOL" (IEEE Transactions on Computational Imaging, in press), and "Dynamic imaging using deep generative SToRM (Gen-SToRM) model" (IEEE Transactions on Medical Imaging, special issue on Deep Learning for Image Reconstruction, in press). He holds major NIH grants, including "Model Based Deep Learning for Ultra-High Resolution Multi-Contrast MRI," "Novel Computational Framework for Free-Breathing & Ungated Dynamic MRI," and "High Resolution MR Spectroscopic Imaging for Alzheimer's Disease and Related Dementias." Awards include Fellow of the IEEE (2022) for contributions to computational biomedical imaging, Shannon Fellow at University of Virginia (2024), Eminent Researcher from Virginia Innovation Partnership Corporation (2024), Distinguished Lecturer of the IEEE Signal Processing Society (2025), NSF CAREER Award (2009), Research Scholar Award from American Cancer Society (2011), and senior authorship on best paper awards at IEEE ISBI (2015, 2019, 2021). He serves as Associate Editor for IEEE Transactions on Medical Imaging, was Associate Editor for IEEE Transactions on Computational Imaging (2016-2020), and General Chair of IEEE International Symposium on Biomedical Imaging (2020).