By Gabby Benedict, CEC Student Reporter

Shijie Zhou of Miami University’s College of Engineering and Computing recently received a $154,000 grant from the American Heart Association for a project that will help clinicians quickly identify where ventricular arrhythmias originally come from.

The project, titled "Automatic Real-time Personalized Non-invasive Ventricular Tachycardia Exit Site Localization System," will develop a personalized non-invasive ventricular tachycardia exit localization approach using 12-lead electrocardiogram (ECG).

Zhou is an assistant professor in the department of Chemical, Paper, and Biomedical Engineering and directs the Computational Clinical Cardiac Electrophysiology Laboratory (CCCEL).

Zhou joined Miami’s faculty in September of last year and has a broad background in engineering and clinical cardiac electrophysiology, including a doctorate in Biomedical Engineering and two masters degrees in Electrical Engineering and Computer Engineering.

Zhou’s research has won various awards, including:

• Cardiac Electrophysiology Society Young Investigator Award (YIA) Finalist (2017 & 2021)
• Heart Rhythm Society (HRS) YIA Finalist (2018) 
• Cardiac Arrhythmia Network of Canada (CANet) Travel Grant (2018 & 2019)
• HRS Travel Grant (2019)
• Third Annual Mark Josephson Competition Finalist in ventricular tachycardia (VT) Symposium (2019)

Moreover, Zhou was awarded the HRS Research Fellowship for 2019-2020 and was named the winner of the Clinical Research Award in Honor of Mark Josephson and Hein Wellens for his proposed project that combined pre-planning CT imaging-based virtual heart technology with real-time ECG data to assist clinical electrophysiologists with the optimal ablation target for scar-related VT.

Zhou was named a Fellow of the Heart Rhythm Society. Election as an HRS Fellow is a major recognition of professional accomplishment from the organization of heart rhythm clinician-scientists. 

In his future as a Fellow, Zhou hopes to research and produce new and improved electrophysiological imaging techniques based on personalized 3D cardiac computational models.

The focus of Zhou's research includes the development of a new generation of cardiac electrophysiological imaging and mapping technologies, based on 3D computational heart models. Personalized simulations, advanced image-based technologies, and real-time ECGs (function data) are employed to improve clinical electrophysiology interventions.

In addition, Zhou also is interested in combining machine learning, clinical cardiac electrophysiology data and computational modeling for clinical pre-planning and outcome prediction.