Research Associate Professor of Internal Medicine - Cardiovascular Medicine
PinMed, Pittsburgh PA and The University of Iowa
Iowa City, Iowa, United States
Vladimir Shusterman is a Research Associate Professor of Internal Medicine - Cardiovascular Medicine at the University of Iowa and President of PinMed, Inc. His focus in the field of magnetic resonance imaging is the development of a high-fidelity, multichannel, wireless, hemodynamic monitoring system with real-time, pattern-recognition-based detection and fiterling of electromagnetic interference generated by MR gradients. An extension of this work is the development of an MRI-compatible defibrillation solution. With the support of the National Institutes of Health, both prototype monitoring and defibrillation systems have undergone successful animal testing.
Dr. Shusterman received an M.D. and a Ph.D. in biomedical engineering from The Novosibirsk State Medical Institute, Novosibirsk, Russia, as well as a B.S. in mathematics from the University of Pittsburgh, Pittsburgh, PA. He served as a Postdoctoral Fellow in biomedical engineering at Tel Aviv University, Israel, and in cardiac electrophysiology and mathematics at the University of Pittsburgh. From 1996 to 2012, Dr. Shusterman served as Director of the Noninvasive Cardiac Electrophysiology Laboratories and an Assistant Professor of Medicine at the University of Pittsburgh Cardiovascular Institute.
Dr. Shusterman's research has been reflected in over 100 peer-reviewed publications and 16 U.S. patents in signal processing, pattern recognition, artificial intelligence, cardiovascular physiology, and the autonomic nervous system. His contributions also include the first measurment of the cardiac electromagnetic field in small animals using a chip-scale, atomic magnetometer developed by NIST, and the development of the first large-scale, mathematically closed and tractable model of cardiovascular homeostasis. Previously, he also studied the precursors of cardiac arrhythmias and the fundamental principles governing the initiation and spread of synchronized rhythmicity in neural networks.
Tracking 12-lead ECG Waveforms during MRI-guided Interventional Procedures and Functional Exams
Thursday, February 5, 2026
10:43 AM - 10:50 AM
