Guoxin Wang is a Postdoctoral Researcher in the School of Electrical & Electronic Engineering at University College Dublin. His research focuses on self- and unsupervised representation learning for physiological time-series, especially electrocardiogram (ECG), and on deploying robust analytics for wearable and edge devices. He co-authored an MAE-based pretraining framework for ECG analysis (IEEE Sensor Journal) and developed an ECG biometric authentication approach using self-supervised learning for IoT edge sensors (2024). Earlier, he worked on continuous user authentication using a genuine wearable chest-strap ECG device (ISCAS 2021). He completed his PhD at UCD, supervised by Avishek Nag and Deepu John.

His research interest includes self-/unsupervised learning for physiological time-series (ECG); wearable sensing and edge AI; efficient deployment (quantization, pruning) and dynamic neural network. He has published high quality papers at the top international journals with google scholar citations .

🔥 News

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📝 Publications

• ECG Biometric Authentication Using Self-Supervised Learning for IoT Edge Sensors, G Wang, S Shanker, A Nag, Y Lian, D John, IEEE Journal of Biomedical and Health Informatics

• A task-generic high-performance unsupervised pre-training framework for ECG, G Wang, Q Wang, A Nag, D John, IEEE Sensors Journal

• More papers on Google Scholar

📖 Educations

• 2019.09 - 2024.12, Ph.D. in Electrical & Electronic Engineering. University College Dublin, Ireland.
• 2015.09 - 2019.06, B.Eng. in Internet of Things. University College Dublin, Ireland.

💻 Internships

• 2018.09 - 2019.09, Chinese Academy of Sciences, China.