Featured Faculty
Linwei Wang
Golisano College of Computing and Information Sciences
LINWEI WANG IS AN ASSISTANT PROFESSOR IN THE PH.D. PROGRAM OF THE GOLISANO COLLEGE OF COMPUTING AND INFORMATION SCIENCES. HER RESEARCH FOCUSES ON THE PROMOTION OF INTEGRATED COMPUTATIONAL, MATHEMATICAL, AND ENGINEERING APPROACHES TO COMPUTATIONAL BIOMEDICINE.
Dr. Wang's lab is interested in the development of an interdisciplinary approach that combines mathematical modeling, system estimation theory and engineering approach, and numerical and computing methods to biomedical problems that are of significance for public health. A proof-of-concept of this philosophy focuses on the development of a novel computational imaging modality that uses noninvasive data to compute electrical propagation path deep beneath the surface of the heart and detects the associated structural / functional causes for arrhythmia.
Electrical waves of the heart spread three-dimensionally throughout the 3D muscle deep beneath the surface of the heart, yet the data available for analysis can only be collected either on our body surfaces (as non-invasive electrocardiograms) or heart surfaces (as invasive electrical maps collected by a catheter inserted in to the chamber of the heart). The inability to access bioelectrical data into the depth of the heart muscle has been the bottleneck to arrhythmia diagnosis and intervention in current practice.
Dr. Wang, along with colleagues, is among the pioneering groups worldwide to demonstrate the success in inferring 3D electrical pathways across the depth of the heart wall. With the initial successes, Dr. Wang along with her doctoral students and colleagues are now devoting their efforts in further pushing the development in the filed of 3D electrical imaging, including developing new mathematical and computing methods to further improve the accuracy of the method, and optimizing the technique to reduce its complexity for future clinical translation. The laboratory has fostered collaborations with Johns Hopkins University School of Medicine, University of Rochester Medical Center, and Dalhousie University (Canada). The long-term success of this research has the potential to transform the clinical practice of arrhythmia management, and to drive scientific discoveries by enabling electromechanical analysis deep beneath the heart surface.