
Wenhao Liang
Higher Degree by Research Candidate
School of Computer and Mathematical Sciences
Faculty of Sciences, Engineering and Technology
My research focuses on developing trustworthy and explainable artificial intelligence (AI) for medical diagnostics, with a particular emphasis on model calibration and reliability. I study how deep learning models can produce not only accurate but also well-calibrated and interpretable predictions that clinicians can trust in critical decision-making processes.
Ultimately, my goal is to build AI systems that are reliable, transparent, and generalizable across medical imaging modalities and clinical environments, enabling safe and responsible deployment of AI in healthcare.
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Conference Papers
Year Citation 2025 Li, Z., Liang, W., Dong, C., Chen, W., & Huang, D. (2025). Correlation Analysis of Adversarial Attack in Time Series Classification. In Q. Z. Sheng, J. Jiang, W. E. Zhang, J. Wu, C. Ma, G. Dobbie, . . . W. Mansoor (Eds.), Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics Vol. 15390 LNAI (pp. 281-296). AUSTRALIA, Sydney: SPRINGER-VERLAG SINGAPORE PTE LTD.
DOI2025 Liang, W., Li, Z., & Chen, W. (2025). Enhancing Financial Market Predictions: Causality-Driven Feature Selection. In Q. Z. Sheng, J. Jiang, W. E. Zhang, J. Wu, C. Ma, G. Dobbie, . . . W. Mansoor (Eds.), ADVANCED DATA MINING AND APPLICATIONS, ADMA 2024, PT I Vol. 15387 (pp. 149-163). AUSTRALIA, Sydney: SPRINGER-VERLAG SINGAPORE PTE LTD.
DOI
My research is supported by the Australian Research Council (ARC) through a competitive PhD Scholarship.
- COMP SCI 7210/7211 -Foundation of Computer Science A/B
- COMP SCI 3314 - Statistical Machine Learning
- COMP SCI 7306 Mining Big Data
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External Profiles