Theme lead / Co-lead
The cluster is led by Professor Dingchang Zheng and Dr Syed Aziz Shah and showcases a multi-disciplinary team of researchers to create innovative and user-friendly healthcare technologies.
Professor Dingchang Zheng (Cluster Lead & Director CIH)
Prof Zheng is a leading research expert in innovative healthcare technology development through the pathway of physiological measurement, bio-signal processing, and technology evaluation. He has published over 200 peer-reviewed scientific papers and earned his international reputation in research and development of novel cardiovascular technologies and devices to address unmet clinical needs, particularly in novel blood pressure and arterial stiffness measurement techniques, and recent developments of wearable devices and IoT monitoring system using unique waveform characteristics derived from physiological signals for monitoring respiration rate, predicting pre-term labour and pregnancy induced hypertension, and developing big-data- centric hearing impairment rehabilitation solution. He has also been well recognized for his enthusiasm in promoting knowledge and technology exchanges, building up educational and research collaborations, and facilitating technology adoption in developing countries, including China, India, Jordan and Nigeria.
Dr Syed Aziz Shah (Cluster Co-Lead and PGR Lead, CIH)
Dr. Syed Aziz Shah was appointed as an Associate Professor in the Research Centre for Intelligent Healthcare (CIH) at Coventry University (CU) in 2020. He is an interdisciplinary researcher focusing on advanced radio frequency (RF) sensor design and signal processing using RF and THz sensing, specifically for healthcare applications. He is highly motivated to utilize and develop advanced technologies that address the unmet healthcare challenges of unobtrusive monitoring of older adult daily activities for health and wellbeing purposes. He is recipient of UK's prestigious Engineering and Physical Sciences Research Council (EPSRC) New Investigator Award. Dr. Aziz also received the endorsement of UK exceptional talent candidate (‘Emerging Leader’) in year 2018, for the pioneering work in the field of wireless sensing for remote patient monitoring. These prestigious awards are given to early-career, world-leadinginnovators and scientists from the Royal Academy of Engineering.
Dr Haipeng Liu (Research Fellow)
Dr Haipeng Liu is a research fellow based within the Centre for Intelligent Healthcare. His research interests include computational simulation of cardiovascular system at macro- and microvascular levels, photoplethysmography and biosignal processing, AI-empowered medical data analysis, and wearable sensor development, with results published on reputed journals including Stroke and Journal of Neurology. He has published 65 scientific papers (index: 17), delivered over 10 invited talks/keynote lectures, and peer-reviewed over 50 papers for more than 20 scientific journals. Dr Liu has the memberships of World Stroke Organization and Chinese Stroke Association. He is currently a supervisor of three PhD students on healthcare sensing and novel medical technologies and keeps exploring new pathways of collaborations on local and international levels.
Dr Yuhang Xu
Dr Xu is currently working as an Assistant Professor at Centre for Intelligent Healthcare, in the theme of Healthcare Sensign Technology. Her research has spanned a wide range of areas within Biomedical Engineering and Electronic Engineering, especially developing advanced signal processing approaches for healthcare applications. She is currently working on the research topics of Preterm Birth Prediction and Pregnancy Monitoring.
Dr Xu was awarded a PhD in Electronic Engineering from King's College London (KCL) in 2018. Her PhD thesis "Advanced Signal Processing Methods for Analysis of Cortico-Muscular Coherence" focuses on analysing electrophysiological signals (EEG and EMG) and developing novel algorithms to aid the classification and stratification of patients with movement disorders. Before working at Coventry University, she worked as a Post-doctoral researcher at the Department of Basic & Clinical Neuroscience and Department of Informatics at KCL on a project to apply the techniques of signal processing, statistics and information theory to predict the epileptic seizures.
In addition to implementing mathematical theories into clinical neuroscience, her previous research has also focused on software development for healthcare applications and communication systems (e.g. Intermediate-Frequency Receiver for Missile Control, Deepwater Communication system).