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

Events

- Obtain a new certification: Oracle AI Vector Search Certified Professional.
- Obtain a new certification: Oracle Cloud Infrastructure 2025 Certified Generative AI Professional.
- Obtain a new certification: Google Advanced Data Analytics.
- Obtain a new certification: Google IT Automation with Python.
- Obtain a new certification: Hugging Face Agents Course.
- Publish a new paper: ECG biometric authentication using self-supervised learning for IoT edge sensors.
- Start a new position: Postdoc at University College Dublin.
- Publish a new paper: A task-generic high-performance unsupervised pre-training framework for ECG.
- Publish a new paper: Unsupervised pre-training using masked autoencoders for ecg analysis.
- Publish a new paper: Continuous user authentication using iot wearable sensors.
- Publish a new paper: Low complexity ecg biometric authentication for iot edge devices.
- Obtained a new certification: Deep Learning Specialization.

📝 Publications

IEEE Journal of Biomedical and Health Informatics

ECG biometric authentication using self-supervised learning for IoT edge sensors

G Wang, S Shanker, A Nag, Y Lian, D John

IEEE Sensors Journal

A task-generic high-performance unsupervised pre-training framework for ECG

G Wang, Q Wang, A Nag, D John

ICTA 2020

Low complexity ecg biometric authentication for iot edge devices G Wang, D John, A Nag
2023 BioCAS

Unsupervised pre-training using masked autoencoders for ecg analysis G Wang, Q Wang, GN Iyer, A Nag, D John

🔍 Service

Reviewer for IEEE transactions on biomedical circuits and systems.

📖 Educations

2019 - 2024 Ph.D in Electrical & Electronic Engineering, University College Dublin
2015 - 2019 B.Eng. in Internet of Things, University College Dublin

hits since Apr. 2024