Research Supervisor Connect
This project focuses on developing AI-empowered IoT systems for healthcare, aiming to enable intelligent, real-time monitoring, diagnosis, and personalised treatment. The research integrates advanced machine learning with IoT sensing platforms to improve efficiency, accuracy, and patient outcomes in digital health.
Electrical and Computer Engineering
The project on Healthcare AI-Empowered IoT seeks to design next-generation intelligent healthcare systems that combine IoT-enabled sensing with advanced artificial intelligence techniques. By leveraging wearable sensors, wireless medical devices, and cloud/edge computing platforms, the research will enable continuous monitoring of physiological signals, early disease detection, and personalised treatment recommendations. The study will focus on developing machine learning and deep learning models capable of handling heterogeneous biomedical data, ensuring reliability, security, and scalability in real-world healthcare applications. Furthermore, the project will explore federated learning and privacy-preserving AI methods to protect sensitive patient information while maintaining high model performance. The outcomes will contribute to advancing smart healthcare solutions for applications such as chronic disease management, elderly care, telemedicine, and clinical decision support.
Research Techniques/Methodologies/Technologies
The project will employ IoT sensing platforms, wearable devices, edge/cloud computing, and AI/ML algorithms (deep learning, federated learning, reinforcement learning) for healthcare data analytics. Data security, interoperability, and real-time system validation will also be core components.
Successful candidates:
The ideal candidate should have a background in electrical/computer engineering, computer science, biomedical engineering, or a related field. Skills in machine learning, IoT systems, or signal processing are highly desirable, along with proficiency in programming (Python, MATLAB, or C/C++). Knowledge of healthcare data standards and an interest in interdisciplinary research bridging engineering and medicine will be advantageous.
How to apply:
To apply, please email [email protected] the following:
The opportunity ID for this research opportunity is 3698