Matthew S. Rosen is an American physicist and professor.
Matthew Rosen | |
|---|---|
 | |
| Nationality | American |
| Alma mater | Rensselaer Polytechnic Institute (BS, Physics), The University of Michigan, Ann Arbor (PhD, Physics) |
| Known for | Ultra-low field MRI
Hyperpolarization Deep Learning for image reconstruction |
| Awards | Fellow, American Physical Society (2020)
Distinguished Investigator, Academy for Radiology & Biomedical Imaging Research (2023) Fellow, International Society for Magnetic Resonance in Medicine (2024) |
| Scientific career | |
| Fields | Physics (Atomic physics), magnetic resonance, Deep learning, optimal control |
| Institutions | Harvard University Center for Astrophysics (2001-2009) MGH/Martinos Center/Harvard Medical School (2009-) |
| Thesis | (2001) |
| Doctoral advisor | Scott D. Swanson (Radiology) Timothy Chupp (Physics) |
After graduating from The Knox School in St. James, New York, in 1988, Rosen completed a bachelor's degree in physics at Rensselaer Polytechnic Institute, followed by a doctorate in the same subject at the University of Michigan.[1][2]
Rosen was elected a Fellow of the American Physical Society in 2021,[3] for his research on "medical imaging through the development and commercialization of low field human MRI scanners,[4][5][6] for the development of automated transform by manifold approximation (AUTOMAP), a general AI-based image reconstruction framework,[7] and for unique spin hyperpolarization techniques." In 2023, he was named Distinguished Investigator by the Academy for Radiology & Biomedical Imaging Research. [8]
Rosen was elected a Fellow of the International Society for Magnetic Resonance in Medicine in 2024 for "outstanding efforts in low-field MRI and development of novel Al-based reconstruction methods leading to the commercialization of novel MRI technologies."[9]
He is a faculty member at the Athinoula A. Martinos Center for Biomedical Imaging and an Associate Professor[10] at Harvard Medical School. He is the Kiyomi and Ed Baird MGH Research Scholar.[11] In 2021, he gave the Paul Callaghan prize lecture at ISMAR.[12] He was the Co-Chair of the 65th Experimental NMR Conference (ENC) in 2024.[13]
In 2014, Rosen, Dr. Jonathan Rothberg, and Professor Ronald Walsworth founded Hyperfine to develop the world's first portable MRI scanner.[4][14][15]
References
edit- ^ "Matthew Rosen, PhD '88". The Knox School. 6 May 2020. Retrieved 21 October 2021.
- ^ "Matthew Rosen". Massachusetts General Hospital. Retrieved 21 October 2021.
- ^ "APS Fellow Archive". American Physical Society. Retrieved 21 October 2021.
- ^ a b Goldsmith, Paul (2021-02-11). "MRI: Going Mobile for the Masses". Massachusetts General Hospital Giving. Retrieved 2021-10-30.
- ^ "USAMRDC: Portable MRI Device Brings Imaging to the Battlefield and Bedside". mrdc.amedd.army.mil. Retrieved 2021-10-30.
- ^ "New Bedside MRI Scanner Inspired by Martinos Center Research | Martinos Center". 2019-10-27. Retrieved 2021-10-30.
- ^ Zhu, Bo; Liu, Jeremiah Z.; Cauley, Stephen F.; Rosen, Bruce R.; Rosen, Matthew S. (March 2018). "Image reconstruction by domain-transform manifold learning". Nature. 555 (7697): 487–492. arXiv:1704.08841. Bibcode:2018Natur.555..487Z. doi:10.1038/nature25988. ISSN 1476-4687. PMID 29565357. S2CID 4173387.
- ^ https://www.acadrad.org/wp-content/uploads/2023/10/DI-2023-Announcement-2.pdf
- ^ Celio, John. "2024 Fellows of the Society". ISMRM. Retrieved 2024-05-06.
- ^ "Matthew Rosen | Martinos Center". 2019-04-05. Retrieved 2022-07-30.
- ^ "MGH Research Scholars 2022-2027". Massachusetts General Hospital. Retrieved 2022-06-20.
- ^ "Prizes: Paul Callaghan Lecture – ISMAR". Retrieved 2023-06-14.
- ^ "ENC - Experimental Nuclear Magnetic Resonance Conference - Conference 2024". www.enc-conference.org. Retrieved 2024-04-17.
- ^ "MRI for all: Cheap portable scanners aim to revolutionize medical imaging". www.science.org. Retrieved 2023-06-13.
- ^ "Hyperfine Begins Trading on the Nasdaq Global Market". ece.umd.edu. Retrieved 2023-06-27.
External links
edit- Matthew Rosen's publications indexed by Google Scholar.
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