CV

Education

• Ph.D. in Computer Science, The University of Melbourne — Faculty of Engineering and Information Technology, School of Computing and Information Systems, Aug 2025 – present
• M.S. in Information Technology (Artificial Intelligence), The University of Melbourne, Feb 2023 – Jun 2024 (with Distinction)
• B.S. in Computer Science, The University of Melbourne, Feb 2020 – Nov 2022

Research interests

• Agent safety
• Trustworthy machine learning

Publications

From Risk Classification to Action Plan Remediation: A Guardrail Feedback Driven Framework for LLM Agents

Yuhao Sun, Jiacheng Zhang, Shaanan Cohney, Zhexin Zhang, Feng Liu, Xingliang Yuan. (2026). "From Risk Classification to Action Plan Remediation: A Guardrail Feedback Driven Framework for LLM Agents." arXiv preprint arXiv:2606.05805.

Let’s Roll a BiFTA: Bi-refinement for Fine-grained Text-visual Alignment in Vision-Language Models

Yuhao Sun, Chengyi Cai, Jiacheng Zhang, Zesheng Ye, Xingliang Yuan, Feng Liu. (2026). "Let's Roll a BiFTA: Bi-refinement for Fine-grained Text-visual Alignment in Vision-Language Models." TMLR 2026.

Be Careful When Fine-tuning On Open-Source LLMs: Your Fine-tuning Data Could Be Secretly Stolen!

Zhexin Zhang, Yuhao Sun, Junxiao Yang, Shiyao Cui, Hongning Wang, Minlie Huang. (2026). "Be Careful When Fine-tuning On Open-Source LLMs: Your Fine-tuning Data Could Be Secretly Stolen!" ICLR 2026.

Sample-Specific Noise Injection For Diffusion-Based Adversarial Purification

Yuhao Sun*, Jiacheng Zhang*, Zesheng Ye, Chaowei Xiao, Feng Liu. (2025). "Sample-Specific Noise Injection For Diffusion-Based Adversarial Purification." ICML 2025. (*Equal contribution)

Academic service

• Reviewer, International Conference on Machine Learning (ICML), 2025, 2026
• Reviewer, International Conference on Learning Representations (ICLR), 2026
• Reviewer, Transactions on Machine Learning Research (TMLR)
• Reviewer, Neural Networks