Staff Profile

Biography

Flora ZHANG earned her Ph.D. degree from City University of Hong Kong in 2025, following which she joined Hong Kong Metropolitan University as a Lecturer. During her Ph.D. studies, she had a five-month visit as a visiting researcher at the University of Tokyo. She previously obtained a Master's degree (Distinction) and a Bachelor's degree (First Class Honours) from University College London.

Teaching Areas & Research Interests

• Deep Learning
• Software Engineering
• Autonomous Driving
• Deep Learning Testing

Selected Publications

Book Chapters

• Zhang, J., Keung, J., Ma, X., Li, X., Xiao, Y., Li, Y., & Chan, W. K. (2024, July). Enhancing valid test input generation with distribution awareness for deep neural networks. In 2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC) (pp. 1095-1100). IEEE.
• Zhang, J., Keung, J., Ma, X., Liao, Y., Li, Y., & 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.
• Zhang, J., Yang, H., Wu, D. J., Keung, J., Li, X., Zhu, X., & Ma, Y. (2023, October). Cross-modal and cross-domain knowledge transfer for label-free 3D segmentation. In Chinese Conference on Pattern Recognition and Computer Vision (PRCV) (pp. 465-477). Singapore: Springer Nature Singapore.
• Wang, Y., Keung, J., Mao, Z., Zhang, J.*, & Cao, Y. (2025, December). Chart2Code-MoLA: Efficient Multi-Modal Code Generation via Adaptive Expert Routing. In 32nd Asia-Pacific Software Engineering Conference (APSEC 2025). IEEE.
• Sun, Y., Keung, J., Zhang, J.*, Yu, H. K., Luo, W., & Liu, S. (2024, July). Unveiling hidden anomalies: Leveraging smac-lstm for enhanced software log analysis. In 2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC) (pp. 1178-1183). IEEE.

Journal Articles

• Zhang, J., Keung, J. W., Xiao, Y., Liao, Y., Li, Y., & Ma, X. (2024). Uniada: Universal adaptive multiobjective adversarial attack for end-to-end autonomous driving systems. IEEE Transactions on Reliability, 73(4), 1892-1906.
• Liao, Y., Keung, J., Zhang, J*., Dai, Y., & Liu, S. (2025). Evaluate Inference Attacks: Attack and Defense against 2D Semantic Segmentation Models. ACM Transactions on Autonomous and Adaptive Systems.
• Liao, Y., Zhang, J.*, Keung, J., Xiao, Y., & Dai, Y. (2025). Advancing autonomous driving system testing: Demands, challenges, and future directions. Information and Software Technology, 107859.

Further Information

Link to personal homepage

Link to Google Scholar page

Modified Date: 30 Jan, 2026
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