Staff Profile

Biography

Kayley Ma earned her Ph.D. degree from City University of Hong Kong in 2024, following which she joined Hong Kong Metropolitan University as a Lecturer. During her doctoral studies, she had a six-month visit as a visiting researcher at University College London. She previously obtained a Master's degree from the Hong Kong University of Science and Technology and a Bachelor's degree (First Class Honours) from Beijing University of Posts and Telecommunications.

I am seeking full-time/part-time RAs to work on automatic log analysis with AI. If you are interested, please send me your latest CV via email.

Teaching Areas & Research Interests

• Data Analytics
• Deep Learning
• Software Engineering

Selected Publications

Book Chapters

• He, Y., Lin, G., Ma, X.*, Keung, J.W., Tan, C., Hu, W. and Li, F., 2024, July. Enhancing Deep Learning Vulnerability Detection through Imbalance Loss Functions: An Empirical Study. In Proceedings of the 15th Asia-Pacific Symposium on Internetware (pp. 85-94).
• Zhang, J., Keung, J., Ma, X.*, Liao, Y., Li, Y. and Sun, Y., 2024, December. Enhancing the Transferability of Adversarial Attacks for End-to-End Autonomous Driving Systems. In 2024 31st Asia-Pacific Software Engineering Conference (APSEC) (pp. 171-180). IEEE.

Journal Articles

• Ma, X., Zou, H., He, P., Keung, J., Li, Y., Yu, X. and Sarro, F., 2024. On the Influence of Data Resampling for Deep Learning-Based Log Anomaly Detection: Insights and Recommendations. IEEE Transactions on Software Engineering, 21(1), pp.243-261.
• Ma, X., Keung, J., He, P., Xiao, Y., Yu, X. and Li, Y., 2023. A Semisupervised Approach for Industrial Anomaly Detection via Self-Adaptive Clustering. IEEE Transactions on Industrial Informatics, 20(2), pp.1687-1697.
• Ma, X., Keung, J.W., Yu, X., Zou, H., Zhang, J. and Li, Y., 2023. AttSum: A deep attention-based summarization model for bug report title generation. IEEE Transactions on Reliability, 72(4), pp.1663-1677.
• Ma, X., Keung, J., Yang, Z., Yu, X., Li, Y. and Zhang, H., 2022. CASMS: Combining clustering with attention semantic model for identifying security bug reports. Information and Software Technology, 147, p.106906.
• Ma, X., Li, Y., Keung, J., Yu, X., Zou, H., Yang, Z., Sarro, F. and Barr, E.T., 2025. Practitioners' expectations on log anomaly detection. IEEE Transactions on Software Engineering, 51(9), pp.2455-2471.
• Ma, X., He, Y., Keung, J., Tan, C., Ma, C., Hu, W. and Li, F., 2025. On the value of imbalance loss functions in enhancing deep learning-based vulnerability detection. Expert Systems with Applications, 291, p.128504.

Further Information

Link to Google Scholar page

Modified Date: 27 Sep, 2025
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