Projects per year
Sami Azam is currently a senior lecturer and researcher with the College of Engineering and IT, Charles Darwin University, Australia. His research expertise includes machine learning, artificial intelligence, deep learning, advanced signal processing and image analysis. Applications include the classification, detection and modelling of a bio signals, such as electroencephalogram (EEG), electrocardiogram (ECG), and acceleration plethysmogram (APG) as well as medical image analysis for skin cancer detection, breast cancer detection and early diagnosis of diabetic and cardiovascular disease. He has also applied machine learning and other artificial intelligence techniques to detect and classify a range of cyber security threats.
A combined framework of interplanetary file system and blockchain to securely manage electronic medical recordsAl Mamun, A., Faruk Jahangir, M. U., Azam, S., Kaiser, M. S. & Karim, A., 2021, Proceedings of International Conference on Trends in Computational and Cognitive Engineering - Proceedings of TCCE 2020. Kaiser, M. S., Bandyopadhyay, A., Mahmud, M. & Ray, K. (eds.). Springer Science and Business Media Deutschland GmbH, p. 501-511 11 p. (Advances in Intelligent Systems and Computing; vol. 1309).
Research output: Chapter in Book/Report/Conference proceeding › Conference Paper published in Proceedings › peer-review
Tatam, M. A., Shanmugam, B., Azam, S. & Krishnan, K., Jan 2021, In: Heliyon. 7, 1, p. 1-19 19 p., e059692.
Research output: Contribution to journal › Article › peer-reviewOpen AccessFile5 Downloads (Pure)
Hamadi, M., El-Den, J., Narumon Sriratanaviriyakul, C. & Azam, S., 1 Jan 2021, In: E-Learning and Digital Media. 18, 1, p. 55-85 31 p.
Research output: Contribution to journal › Article › peer-reviewOpen AccessFile2 Downloads (Pure)
Cognitive learning environment and classroom analytics (cleca): A method based on dynamic data mining techniquesAl Karim, M., Karim, A., Azam, S., Ahmed, E., De Boer, F., Islam, A. & Nur, F. N., 3 Feb 2021, Lecture Notes on Data Engineering and Communications Technologies. Singapore: Springer Singapore, Vol. 59. p. 787-797 11 p. (Lecture Notes on Data Engineering and Communications Technologies; vol. 59).
Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review
Efficient prediction of cardiovascular disease using machine learning algorithms with relief and lasso feature selection techniquesGhosh, P., Azam, S., Jonkman, M., Karim, A., Shamrat, F. M. J. M., Ignatious, E., Shultana, S., Beeravolu, A. R. & De Boer, F., 22 Jan 2021, In: IEEE Access. 9, p. 19304-19326 23 p., 9333574.
Research output: Contribution to journal › Article › peer-reviewOpen AccessFile33 Downloads (Pure)