Projects per year
Personal profile
Biography
Dr Wanli Ma received his PhD degree in Computer Science and Technology from the Australian National University, Canberra, Australia, in 2001.
He had 8 years first hand experience in running IT infrastructure, IT security operations, and digital forensic investigation before joining the Faculty of Information Sciences and Engineering in January 2004.
His research areas are of application nature and mainly concentrate on the application of machine learning and artificial intelligence techniques into cyber security, anomaly (intrusion, spam email, and virus, etc.) discovery and detection, Internet identity management, digital evidence gathering and analysis, and human biological signals.
Research interests
- Machine learning and data mining
- eHealth and IT security
- Digital forensics
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Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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CSSS: Indigenous, micro, small and medium business cybersecurity standards ontology
Romano, R., John, B., Barkat Ullah, A., Ma, W. & Awasthy, R.
1/01/23 → 31/12/23
Project: Research
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Cyber Security Standards (ISMS) Research on Australian mining and mineral industries
Barkat Ullah, A., Ma, W. & Ahmed, M.
1/07/21 → 31/10/21
Project: Research
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Enhancing Interactions using Vision and Depth based Techniques (HDR student Stuart James Anderson)
1/04/13 → 31/03/16
Project: Other
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A novel application of deep learning to forensic hair analysis methodology
Airlie, M., Robertson, J., Ma, W., Airlie, D. & Brooks, E., 29 Dec 2022, In: Australian Journal of Forensic Sciences. p. 1-12 12 p.Research output: Contribution to journal › Article › peer-review
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Application of Deep Learning in Automated Meal Recognition
Mao, J., Tran, D., Ma, W., Naumovski, N., Kellett, J., martinez-marroquin, E. & Slattery, A., 5 Jan 2021, 2020 IEEE Symposium Series on Computational Intelligence (SSCI). Abbass, H., Coello Coello, C. A. & Singh, H. K. (eds.). United States: IEEE, Institute of Electrical and Electronics Engineers, p. 58-63 6 p. 9308482. (2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020).Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review
1 Citation (Scopus) -
Biometric recognition system performance measures for lossy compression on EEG signals
Nguyen, B., Ma, W. & Tran, D., 1 Dec 2021, In: Interest Group in Pure and Applied Logics. Logic Journal. 29, 6, p. 889–905 17 p.Research output: Contribution to journal › Article › peer-review
1 Citation (Scopus) -
Static Analysis for Android Malware detection with Document Vectors
Raghav, U., Martinez-Marroquin, E. & Ma, W., 2021, Proceedings - 21st IEEE International Conference on Data Mining Workshops, ICDMW 2021. Xue, B., Pechenizkiy, M. & Koh, Y. S. (eds.). United States: IEEE, Institute of Electrical and Electronics Engineers, p. 805-812 8 p. (IEEE International Conference on Data Mining Workshops, ICDMW; vol. 2021-December).Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review
1 Citation (Scopus) -
Wavelet-based denoising for EEG-based pattern recognition systems
Nguyen, B., Ma, W., Tran, D. & Chung, Y., 1 Dec 2020, 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020. Abbass, H., Coello Coello, C. A. & Singh, H. K. (eds.). United States: IEEE, Institute of Electrical and Electronics Engineers, p. 1249-1256 8 p. 9308421. (2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020).Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review
1 Citation (Scopus)