Dr Argha received his BSc and MSc in Electrical Engineering from Shiraz University, Iran, and his PhD from University of Technology Sydney (UTS), Australia (2016). He is currently a Postdoctoral Research Fellow at the Graduate School of Biomedical Engineering, UNSW, Sydney, using his skills in biomedical system modelling and control, signal processing, data analysis and machine learning. Reza has an advanced knowledge of machine learning and deep learning and has applied his knowledge to biosignal processing and analytics. Within this scope, his effort was to pioneer AI-based methods to model complexity of physiological data and thereby develop novel predictive algorithms. Specifically, he pioneered the application of convolutional and recurrent neural networks in non-invasive blood pressure (NIBP) estimation from oscillometric and auscultatory waveforms and ECG arrhythmia classification using single-lead short-term ECG waveforms. He obtained a UNSW Translational Seed Fund for the development of an AI-based NIBP estimation device.
In 2021, in collaboration with other CIs he was able to secure a large ($5 M) ARC Research Hub for Connected Sensors for Health grant. In 2020, in collaboration with other researchers from UNSW Sydney and POWH, he was able to secure a large MRFF grant ($1.7 M) Cardiovascular Health Mission 2019 Grant to address the MRFF Cardiovascular Health Mission Priority 3: improving secondary prevention and survivorship after a cardiovascular event. He has developed data-driven-based clinical decision support systems for abnormality detection in ECG data collected via wearable electronic devices. As a CI, he was also successful in obtaining an SPHERE Seed Funding Grant for a proposed project entitled Ambulatory Monitoring and Management of COPD in the Community, and two other Seed Funding Grant for the development of unobtrusive fall detection systems (Catalyst Award from IHealthE and a Seed Funding from Ageing Future Institute, UNSW).
Email: a.argha@unsw.edu.au