🙋 Zhiqiang Huo (霍志强) is a Lecturer (Teaching & Research) in Health Data Science at the Wolfson Department of Population Health, Queen Mary University of London, UK. He was funded by Barts Health Trust to leverage artificial intelligence (AI) to unlock the full longitudinal phenotypic information embedded in electronic health records (EHRs) for millions of residents in Northeast London. This work aims to enhance clinical decision-making systems and improve the quality of life for patients. He is also a Visting Lecturer at King’s College London.

🕵 Zhiqiang is passionate about developing AI-powered, data-driven decision-making systems, leveraging digital technology to drive innovation in interdisciplinary research across healthcare and engineering. His research interests include big data analysis, machine learning, time series complexity analysis, signal processing, Internet of Things, and digital technology (co-production with stakeholders).

📝 He has published over 50 papers in leading peer-reviewed international journals and conferences, including npj Digital Medicine (nature portfolio), Intensive Care Medicine – Paediatric and Neonatal, IEEE Transactions on Instrumentation and Measurement, IEEE Internet of Things Journal, IEEE/ASME Transactions on Mechatronics, and IEEE Industrial Electronics Magazine.

🎓Zhiqiang obtained his MSc and BSc degrees in Computer Science and Technology from China University of Geosciences, Beijing, China. He earned his PhD in AI-driven industrial machinery health condition monitoring from the University of Lincoln (2016–2020). After completing his PhD, he worked as a Research Fellow at the Institute of Health Informatics, University College London, UK (2020–2022) and later as a Research Associate at the Department of Population Health Sciences, King’s College London, UK (2022–2025).