Russell Posner

ferroptosis; oncology; magnetic resonance spectroscopy

Russell is a resident physician in the Department of Radiology whose background is in applied mathematics and computer science. His doctoral work studied principles regulating gene expression and cell differentiation trajectories as well as methods in deep learning and image reconstruction. Russell is a relative newcomer to MR spectroscopy, but looks forward to using his skills to help bring the lab’s tools and techniques into the clinical domain.

Russell joined the MR SCIENCE laboratory in 2022 to work on development of metabolomic profiling of tissues using MR spectroscopy. His goal is to apply methods in radiology to diseased tissues of the pancreas to noninvasively diagnose cancers and quantify treatment response.

Pronouns – he/him

Resident Physician, Department of Radiology, New York Presbyterian Hospital – Columbia University Irving Medical Center (2022-present)
Transitional Year Intern, Manchester Memorial Hospital, Manchester, CT (2021-2022)

M.D.                     University of Connecticut School of Medicine (2021)
Ph.D.                    in Systems Biology, University of Connecticut (2021)
M.S.                      in Mathematics, Courant Institute of Mathematical Sciences (2010)
B.S., B.A.             in Mathematics and Chemistry, Duke University (2008)

Healthcare Case Competition at The Jackson Laboratory - 1st place (2016)
Yale School of Management Healthcare Case Competition - 3rd place (2016)
Howard Hughes Fellowship in Mathematical Biology (2007)
COMAP Mathematical Contest in Modeling, Outstanding Award (2007)

Bai J, Posner R, Wang T, Yang C, Nabavi S. Applying deep learning in digital breast tomosynthesis for automatic breast cancer detection: A review. Medical Image Analysis, Volume 71 (2021).
Russell Posner and Reinhard Laubenbacher. The contribution of microRNA-mediated regulation to short- and long-term gene expression predictability. Journal of Theoretical Biology, vol. 486 (2020).
Russell Posner and Reinhard Laubenbacher. Connecting the molecular function of microRNAs to cell differentiation dynamics. Journal of the Royal Society Interface, vol. 16 issue 185 (2019).