Reza Argha

He is currently a Senior Lecturer at the School of Biomedical Engineering, UNSW Sydney, where he applies expertise in biomedical system modelling and control, signal and image processing, health data analytics, and artificial intelligence. Reza has advanced knowledge of machine learning and deep learning and applies these methods to multimodal biomedical data, including biosignals, medical images, and clinical records. His recent research focuses on the use of large language models for developing foundation models and multimodal learning frameworks that integrate language with images, physiological signals, and other health data for clinical decision support, health analytics, and unobtrusive monitoring. His work aims to model the complexity and heterogeneity of physiological data to enable robust prediction, interpretation, and next-generation digital health systems. deep learning, machine learning, health data science, activity monitor, biomedical signal processing, biomedical engineering, medical image processing