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Ying Wang is an Assistant Professor at the University of Twente, specializing in Biomedical Signals Systems (BSS). His research focuses on Hybrid Artificial Intelligence Physiological Mechanistic Models for daily-life health monitoring, integrating simplified mechanistic models with interacting organ systems. He aims to develop monitoring methods that perform robustly in real-world conditions and are interpretable by clinicians, catering to personalized health needs. Wang addresses the limitations of current digital health technologies, particularly those based solely on black-box AI or physiology-only models. He leads several research projects including the MSCA Doctoral Network SMARTTEST, which is aimed at developing algorithms for multimodal signal analysis for health monitoring. His work also involves projects related to stress monitoring, resilience in older adults, and daily-life algorithms for managing conditions like osteoarthritis and diabetes. He has supervised numerous PhD candidates and contributes actively to the academic community as a committee member of the Dutch Electrical Engineering Council and as a reviewer of research protocols. Wang's expertise includes Medicine, Nursing, Heart Rate Variability, and the use of wearable sensing and signal analysis for practical clinical applications.
University of Twente • Enschede, Netherlands
Assistant Professor in Biomedical Signals Systems, focusing on health monitoring technologies and algorithms.
Includes specializations in Financial Engineering & Management, Healthcare Technology & Management, and Production & Logistics Management.