Xin Li

Xin Li is a Lecturer in Biomedical Engineering at the University of Leicester, jointly appointed at the School of Engineering and the Department of Cardiovascular Sciences. He holds a BEng in Electrical Information Engineering (University of Science and Technology Beijing, 2011), an MSc in Electrical Electronic Engineering (University of Leeds, 2012), and a PhD in Biomedical Engineering (University of Leicester, 2016). His research focuses on advanced signal processing techniques for cardiac arrhythmias, machine learning applications in biomedical engineering, and wearable medical devices for remote monitoring. Specific interests include P-wave analysis for atrial fibrillation ablation outcomes, sudden cardiac death risk prediction, and non-invasive cardiac imaging techniques.

His work integrates computational methods, clinical data, and biomedical engineering to improve diagnostic tools and therapeutic strategies. Notable projects include developing AI-driven Holter monitors for arrhythmia detection and optimizing catheter ablation protocols using electrogram features. He collaborates across disciplines, bridging engineering and clinical cardiology.

Research highlights include studies on body surface potential mapping for atrial fibrillation recurrence prediction and the role of wearable devices in healthcare. His lab focuses on translational research, aiming to transition innovations into clinical practice.