Elizabeth
Cherry
Associate Professor, Associate Chair for Academic Affairs, Computational Science and Engineering
Elizabeth Cherry is an Associate Professor in the School of Computational Science and Engineering. Her research involves modeling and simulation, high-performance computing, and numerical methods. In particular, her group is focused on computational modeling of cardiac arrhythmias, including model development, validation, and parameter estimation; design and implementation of efficient solution methods; implementations on traditional parallel and GPGPU architectures; integration with experiments through data assimilation; and applications to understand the mechanisms responsible for particular complex dynamical states. She is a member of the editorial board of Chaos and a review editor for Frontiers in Physiology. She has served on the organizing committees of the SIAM Conference on Applications of Dynamical Systems in 2017, Dynamics Days 2020, and the Biology and Medicine Through Mathematics Conference 2018 and 2019 and on the program committees for the International Workshop on Hybrid Systems 2019 and 2020 and the International Congress on Electrocardiology 2018 and 2019. She received a BS in Mathematics from Georgetown University and a PhD in Computer Science from Duke University focusing on efficient computational methods for solving partial-differential-equations models of electrical signals in the heart. Her research is supported by the National Science Foundation and the National Institutes of Health.
Research Interests
My main area of research is the interdisciplinary field of computational cardiac electrophysiology and arrhythmias. Essentially, I use computational modeling and simulation to improve the understanding of cardiac dynamics in normal and diseased states and to design advanced strategies for prevention and treatment of arrhythmias.
Gaining new insights into cardiac electrical dynamics and the dangerous arrhythmias that can develop in the heart is an important challenge. Sudden cardiac death resulting from disruptions to the heart’s normal rhythm remains the leading cause of death in the industrialized world, causing about 20 percent of all deaths. Research has shown that the most dangerous cardiac arrhythmias arise from reentrant waves corresponding to spiral or scroll waves of electrical activity within the heart. Because the frequencies of these reentrant waves are higher than the heart's natural pacemaker frequency, the heart’s normal rhythm is disturbed, triggering mechanical dysfunction that prevents adequate contraction and pumping of blood. Arrhythmias may be more likely to occur when certain diseases are present, but they can arise even in individuals with no diagnosed heart disease. Despite the medical importance, much remains to be understood about the mechanisms responsible for the formation and evolution of arrhythmias in human hearts. Although traditional experiments and clinical work are necessary, computational and mathematical models of cardiac electrical processes and numerical simulations of these models have been used for several decades to derive new insights into and deeper understanding of normal and abnormal cardiac cell and tissue behavior.
I am involved in research at the leading edge of several aspects of this area, including advanced computational methods, model development and analysis, and physiological applications of modeling to interpret experimental and clinical observations. New insights from this work have the potential to improve understanding and to lead to better treatment strategies for several types of cardiovascular disease; they also should extend to related physiological systems.