Yingchun Zhang, PhD

  • Source: Scopus
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Personal profile

Personal profile

Dr. Zhang earned his Ph.D. in Electrical Engineering from Zhejiang University, China in 2004. He held a faculty appointment at the University of Minnesota, Minneapolis before joining the faculty of the University of Houston in 2012 and becoming an assistant affiliate member of Houston Methodist Research Institute in 2014. Dr. Zhang is currently an Assistant Professor in the Department of Biomedical Engineering at the University of Houston. He directs a predictive modeling and functional imaging research program focusing on clinical diagnosis technology of urogenital dysfunction and other disorders in the human body through the fusion of functional bioelectrical activity/impedance imaging, electrical stimulation and recording, advanced computational modeling and electrophysiological/biomechanical analysis. Dr. Zhang is a recipient of NIH Pathway to Independence (K99/R00) award, an IEEE senior member and serves as a reviewer for a number of peer-review scientific journals.

Research interests

Dr. Zhang’s Predictive Modeling and Functional Imaging Lab is interested in advancing clinical diagnosis of dysfunction in the human body through the fusion of functional bioelectrical activity/property imaging, neuromodulation, advanced computational modeling and electrophysiological/biomechanical analysis with applications in investigating the mechanisms of bioelectrical activities and neural pathways in biological systems. His lab is also interested in utilizing developed functional imaging technologies to enhance human-machine-interface systems such as brain-computer-interface systems, brain-controlled devices and myoelectrically-controlled prostheses. The research in his lab involves both technology developments and experimental studies in human subjects and animals.

Education/Academic qualification

MS, Harbin Institute of Technology

Biomedical Engineering, Postdoctoral Fellowship, University of Minnesota

Electrical Engineering, PhD, Zhejiang University

Free-text keywords

  • Multimodal neural imaging
  • Predictive modeling
  • Incontinence
  • Rehabilitation
  • Prostate cancer early detection

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