Fields of Research (FoR)Biomedical engineering, Health informatics and information systems, Machine learning, Deep learning, Artificial intelligence, Signal processing, Digital health, Aged health care, Control Systems, Robotics and Automation, Biomedical Engineering, Biomedical Instrumentation, Rehabilitation Engineering, Health Informatics, Pattern Recognition and Data Mining, Computer Vision
He is currently a Lecturer 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 is to pioneer AI-based methods to model complexity of physiological data...view more
He is currently a Lecturer 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 is to pioneer AI-based methods to model complexity of physiological data and thereby develop novel predictive algorithms.
- ARC Research Hub for Connected Sensors for Health, ARC Industrial Transformation Research Hubs ($5m)
- A novel device for error free estimation of blood pressure, UNSW Translational Seed Fund ($72k)
- Machine learning-based electrocardiographic analysis to predict sudden cardiac death in patients with hypertrophic cardiomyopathy, CVMM Collaborative Grant 2024 ($30k)
- Machine learning-based electrocardiographic analysis to predict cardiac toxicity in patients undergoing cancer treatment, CVMM Collaborative Grant 2023 ($30k)
- Development of a Living Lab and Artificial Intelligence Models for Multi-person Human Pose Estimation, Activity Recognition and Human-Human Interaction Recognition Using mmWave Radar Technology, Ageing Future Institute and Tyree Foundation Institute of Health Engineering ($60k)
- Guardian Angels – unobtrusive fall detection for persons living with dementia, Tyree Foundation Institute of Health Engineering ($30k)
- Development of an unobtrusive fall detection system for older people using artificial intelligence and mmWave radar, Ageing Future Institute, UNSW ($30k)
- GROW Early Career Academics Grant program ($40k)
Dr Argha received his BSc and MSc in Electrical Engineering from Shiraz University, Iran, and his PhD from University of Technology Sydney (UTS), Australia (2017).
Reza’s PhD thesis was included in the Chancellor’s list for 2017 Chancellor’s award for best PhD thesis, which acknowledges his doctoral thesis judged to be of the highest calibre among all the University of Technology Sydney’s theses. He was also twice awarded the UTS FEIT Higher Degree Research Publication Award (2014 and 2015) based on a competitive application related to research capacity and a UTS Faculty of Engineering Research Excellence Award. In 2013 and 2014, during his PhD, he was awarded student travel awards by the conference organisers to attend the IEEE Australian Control Conference (Perth, 2013) and IEEE Annual Conference on Decision and Control (LA, USA, 2014). He also received an Australian Postgraduate Award (APA) Scholarship in 2013, and during his PhD, he received a flagship top-up scholarship from the CSIRO to build an automated exercise testing system by designing a novel control mechanism for cycle-ergometers.
My Research Activities
- Development of data-driven algorithms for fall detection and prediction using infrared sensors and mmWave radar
- Development of deep-Learning based algorithms for non-invasive blood pressure estimation
- Development of deep-Learning based algorithms for arrhythmia detection through single-lead short-term ECG waveforms
- Clinical decision support systems for telehealth systems
- Human-in-the-Loop control systems
- Smart home IT support for frail elderly people with early dementia who live alone
My Research Supervision
Areas of supervision
I am currently looking at accepting new students in the areas of digital health, health data analytics, bisignal and image processing, telehealth systems and AI-based clinical decision support systems for managing chronic disease, and next generation data driven fall detection and prediction systems using radar technology.
I have supervised one student to successful completion and am currently supervising and co-supervising 6 PhD students.
Biological Signal Analysis (BIOM9621)
Engineering Vertically Integrated Projects (ENGG2600/3600/4600)