Jonathan Martin, Ph.D.

Research Assistant Professor
Dept. of Radiology and Radiological Sciences

Jonathan Martin, Ph.D., is a Research Assistant Professor in the Department of Radiology and Radiological Sciences at Vanderbilt University Medical Center. He earned his B.S. in Electrical Engineering at the University of Virginia, and his Ph.D. in Biomedical Engineering from Vanderbilt University in 2023, supervised by Dr. William Grissom. Following his graduate education, he trained as a postdoctoral researcher with Drs. John Gore and Kevin Harkins at Vanderbilt University Medical Center. He was awarded a five-year NIH National Heart Lung and Blood Institute (NHLBI) K25 Mentored Research Scientist Career Development grant and was promoted to the faculty in 2026.

Dr. Martin’s research focuses on developing ultra-low field (ULF) MRI as a route to new accessible medical imaging applications. His current research areas include a) cardiovascular MRI at ULF, b) radiofrequency field gradient encoding, and c) AI for improved image acquisition and mitigation of imaging system imperfections. He also strives to develop open-source software tools in support of accessible ULF MRI.

Publications

C.R. Sappo, M.A. Barron, R.T. Constable, G. Galiana, A.R. Purchase, S. Srinivas, E. Torres, C.E. Vaughn, and J.B. Martin. "Radiofrequency field gradient encoding methods and applications for magnetic resonance imaging," Magnetic Resonance Imaging, 2026, https://doi.org/10.1016/j.mri.2026.110788.

J. B. Martin, H. E. Alderson, J. C. Gore, M. D. Does, and K. D. Harkins, “ Modeling the MRI gradient system with a temporal convolutional network: Improved reconstruction by prediction of readout gradient errors,” Magnetic Resonance in Medicine 95, no. 1 (2026): 286–298, https://doi.org/10.1002/mrm.70044.

Martin JB, Sun H, Albert M, Johnson KM, Grissom WA. "PulPy: A Python Toolkit for MRI RF and Gradient Pulse Design." J Open Source Softw. 2024;9(103):6586. doi: 10.21105/joss.06586. Epub 2024 Nov 1. PMID: 40881849; PMCID: PMC12381754.

Martin, JB, Kurmi, Y, and Sappo, CR. "LoFi RADIO: A Distilled In-Domain Backbone Applied for Artifact-Severity Grading of Ultra-Low-Field Neonatal Brain MR." arXiv preprint arXiv:2609.02676, 2026.

Martin JB, Srinivas SA, Vaughn CE, Sun H, Griswold MA, Grissom WA. Selective excitation localized by the Bloch-Siegert shift and a B1+ gradient. Magn Reson Med. 2022 Sep;88(3):1081-1097. doi: 10.1002/mrm.29271. Epub 2022 Apr 25. PMID: 35468232; PMCID: PMC9246893.