Profile

Education:

She received her BE (Electronics) degree from UCD and Beijing University of Technology in 2019. Her undergraduate major was Internet of Things (IoT). She is currently pursuing her Ph.D. degree with the Department of Electrical and Electrotonic Engineering, University College Dublin, Dublin, Ireland.

Research Interests:

Continuous monitoring of vital physiological signals like Electrocardiogram (ECG), using wearable devices for early detection and preventive action is widely regarded as a solution to the costs and risks associated with cardiovascular disease. While the concept itself is not new, continuous monitoring of medical-grade physiological signals has yet to become a reality. One of the major challenges involved is the high-power consumption of continuous wireless transmission, which makes the device too large for continuous use.

Her research aims to solve this problem by developing distributed machine learning technology, in which the preliminary classification of physiological signals is completed locally in the sensor and the rest is completed on the cloud server. Wireless transmission is enabled only when it is deemed necessary, based on initial processing. The topic is to develop powerful, accurate, fast and low-cost methods for identifying arrhythmia events in distributed wearable sensor data.