I am an early-career researcher with an interdisciplinary background in Computer Science, Mechanical Engineering, and Health Informatics. My research focuses on harnessing data-driven decision-making, machine learning (ML), artificial intelligence (AI), and signal processing to address real-world healthcare challenges. These interests have driven my work in healthcare informatics, where I aim to develop digital solutions that improve patient care, diagnosis, and treatment outcomes.

Currently, I am a Research Associate at King’s College London (KCL), working on the NIHR-funded programme titled “Improving the lives of stroke survivors with data.” In this role, I contribute to the design and development of a patient-centred data portal and research dashboard for stroke survivors. By applying data/AI support, our team works on improving decision-making processes associated with stroke patient monitoring, care, and prediction. The project aims to enhance patient outcomes by delivering a robust, data-driven solution that engages all stakeholders, including patients, caregivers, clinicians, and policymakers.

My previous role at University College London has involved leading and collaborating on significant healthcare projects, such as the UCL-CATS-GOSH-Kinseed pilot study, which utilized high-frequency vital signs and EHR data to monitor critically ill children, involving a collaboration with engineers, AI scientists and intensive care clinicians. These experiences, combined with my expertise in signal processing and time-series analysis, have resulted in impactful research outputs and high-quality publications in leading journals.

In addition to my publication experience, I have demonstrated leadership by supervising graduate students, co-authoring over 50 peer-reviewed papers, and securing funding for small grants to support my research development. I am passionate about using AI and digital health solutions to address critical healthcare challenges, and my goal is to generate meaningful, long-term impacts in improving patient outcomes and healthcare delivery.

I have been serving to the academic community as Guest Editor on  "Health Data Science and AI in Neuroscience & Psychology", Frontiers in Computational Neuroscience, 2024; Guest Editor on "State Estimation and Fault Diagnosis of Energy Systems Based on Artificial Intelligence", Recent Advances in Computer Science and Communications, Bentham Science, 2024; and Program Committee Member in international conferences for 8 times; active reviewers for high-quality peer-reviewed journals, such as IEEE Transactions on Instrumentation and Measurement (IF: 5.6), IEEE Transactions on Industrial Informatics (IF: 9.112); IEEE-CAA Journal of Automatica Sinica (IF: 5.129) and IEEE Systems Journal (IF: 3.987).

More information about my publication, professional services and project experience can be found from:

• Personal website: www.zqhuo.com
• Google Scholar
• Linkedin