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Sami Azam is a Senior Lecturer and Course Coordinator for the Faculty of Science and Technology at Charles Darwin University. Holding a PhD in Biomedical Engineering, Dr Azam conducted research on the detection of binaural processing in the human brain during his doctoral studies. His expertise spans various domains, including machine learning, artificial intelligence, deep learning, advanced signal processing, image analysis, and explainable AI. Throughout his career, he has leveraged his knowledge to develop and implement state-of-the-art machine learning models for automated detection, classification, and prediction of data patterns using images and diverse datasets. Applications include the classification, detection and modelling of biosignals, such as electroencephalogram (EEG), electrocardiogram (ECG), and acceleration plethysmogram (APG) as well as medical image and clinical data analysis for early diagnosis of disease. He has also applied his expertise in machine learning and artificial intelligence to address critical issues in data security and the Internet of Things (IoT). He has explored frameworks to enhance privacy and security in electronic health records, aiming to reduce the occurrence of data breaches. He is a key member of the Biomedical Engineering and Health Informatics research group at Charles Darwin University and is a long-term resident of the Northern Territory.
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Collaborations and top research areas from the last five years
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Integrating emerging aviation technology into ghost-net detection, survey, and retrieval operations around the Groote Archipelago
1/03/23 → 31/03/25
1/07/22 → 31/12/23
Rainmaker Start-up: Creating a permanent and verifiable digital identity using block chain technology
4/10/19 → 30/11/20
A Computer-Aided Diagnostic System to Identify Diabetic Retinopathy, Utilizing a Modified Compact Convolutional Transformer and Low-Resolution Images to Reduce Computation TimeKhan, I. U., Raiaan, M. A. K., Fatema, K., Azam, S., Rashid, R. U., Mukta, S. H., Jonkman, M. & De Boer, F., Jun 2023, In: Biomedicines. 11, 6, p. 1-27 27 p., 1566.
Research output: Contribution to journal › Article › peer-reviewOpen AccessFile8 Downloads (Pure)
A Lightweight Robust Deep Learning Model Gained High Accuracy in Classifying a Wide Range of Diabetic Retinopathy ImagesRaiaan, M. A. K., Fatema, K., Khan, I. U., Azam, S., Rashid, M. R. U., Mukta, M. S. H., Jonkman, M. & De Boer, F., 2023, In: IEEE Access. 11, p. 42361-42388 28 p.
Research output: Contribution to journal › Article › peer-reviewOpen AccessFile31 Downloads (Pure)
AlzheimerNet: An Effective Deep Learning Based Proposition for Alzheimer's Disease Stages Classification From Functional Brain Changes in Magnetic Resonance ImagesShamrat, F. M. J. M., Akter, S., Azam, S., Karim, A., Ghosh, P., Tasnim, Z., Hasib, K. M., De Boer, F. & Ahmed, K., 2023, In: IEEE Access. 11, p. 16376-16395 20 p.
Research output: Contribution to journal › Article › peer-reviewOpen AccessFile33 Downloads (Pure)
A machine learning approach for risk factors analysis and survival prediction of Heart Failure patientsAli, M. M., Al-Doori, V. S., Mirzah, N., Hemu, A. A., Mahmud, I., Azam, S., Al-tabatabaie, K. F., Ahmed, K., Bui, F. M. & Moni, M. A., Nov 2023, In: Healthcare Analytics. 3, p. 1-12 12 p., 100182.
Research output: Contribution to journal › Article › peer-reviewOpen AccessFile16 Downloads (Pure)
Fayyaz, A. M., Sharif, M. I., Azam, S., Karim, A. & El-Den, J., Jan 2023, In: Information (Switzerland). 14, 1, p. 1-14 14 p., 30.
Research output: Contribution to journal › Article › peer-reviewOpen AccessFile25 Downloads (Pure)
Azam, S., 2016
Student thesis: Doctor of Philosophy (PhD) - CDUFile