Zihao Zhu

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zihaozhu@link.cuhk.edu.cn

Hi, this is Zihao Zhu (朱梓豪). I am currently a Ph.D. candidate in Data Science at The Chinese University of Hong Kong, Shenzhen, under the supervision of Prof. Baoyuan Wu. During my Ph.D., I have been closely collaborating with Prof. Siwei Lyu at the University at Buffalo, SUNY. Previously, I received my Master’s degree from the Institute of Information Engineering at the University of Chinese Academy of Sciences in 2021, and my Bachelor’s degree from China University of Mining and Technology in 2018.

My research focuses on Trustworthy AI, encompassing the safety and reliability of AI systems across multiple dimensions. Specifically, my work covers LLM safety and alignment, reasoning model robustness, embodied AI agent safety, data governance, and adversarial and backdoor attack/defense.

I am currently on the job market and seeking full-time opportunities in academia or industry. I would be delighted to connect if you have relevant openings or suggestions.

News

Jan 30, 2026 Two papers have been accepted to ICLR 2026!
Sep 25, 2025 One open-source project I participated in “Loong: Synthesize Long Chain-of-Thoughts at Scale through Verifiers” has been accepted to NeurIPS 2025 workshop on LAW!
Sep 25, 2025 Our work “To Think or Not to Think: Exploring the Unthinking Vulnerability in Large Reasoning Models” has been accepted to NeurIPS 2025 workshop on FoRLM!
Sep 10, 2025 Our survey “Defenses in adversarial machine learning: A survey” has been accepted to IEEE TPAMI! :rocket:
Sep 01, 2025 Our survey “Attacks in adversarial machine learning: A systematic survey from the life-cycle perspective” has been accepted to IJCV! :rocket:

Selected Publications (Full)

  1. ICLR
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    AdvChain: Adversarial Chain-of-Thought Tuning for Robust Safety Alignment of Large Reasoning Models
    Zihao Zhu , Xinyu Wu, Gehan Hu, Siwei Lyu, Ke Xu, and Baoyuan Wu
    In International Conference on Learning Representations (ICLR), 2026
  2. ICLR
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    Reliable Poisoned Sample Detection against Backdoor Attacks Enhanced by Sharpness Aware Minimization
    Mingda Zhang, Mingli Zhu, Zihao Zhu , and Baoyuan Wu
    In International Conference on Learning Representations (ICLR), 2026
  3. NeurIPS
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    To Think or Not to Think: Exploring the Unthinking Vulnerability in Large Reasoning Models
    Zihao Zhu , Hongbao Zhang, Ruotong Wang, Xu Ke, Lyu Siwei, and Baoyuan Wu
    In NeurIPS 2025 Workshop on Foundations of Reasoning in Language Models, 2025
  4. TPAMI
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    Defenses in adversarial machine learning: A survey
    Baoyuan Wu, Mingli Zhu, Meixi Zheng, Zihao Zhu , Shaokui Wei, Mingda Zhang, Hongrui Chen, Danni Yuan, Li Liu, and Qingshan Liu
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2025
  5. TPAMI
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    BlackboxBench: A Comprehensive Benchmark of Black-box Adversarial Attacks
    Meixi Zheng, Xuanchen Yan, Zihao Zhu , Hongrui Chen, and Baoyuan Wu
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2025
  6. IJCV
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    BackdoorBench: A Comprehensive Benchmark and Analysis of Backdoor Learning
    Baoyuan Wu, Hongrui Chen, Mingda Zhang, Zihao Zhu , Shaokui Wei, Danni Yuan, Mingli Zhu, Ruotong Wang, Li Liu, and Chao Shen
    International Journal of Computer Vision (IJCV), 2025
  7. ICLR
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    VDC: Versatile Data Cleanser based on Visual-Linguistic Inconsistency by Multimodal Large Language Models
    Zihao Zhu , Mingda Zhang, Shaokui Wei, Bingzhe Wu, and Baoyuan Wu
    In International Conference on Learning Representations (ICLR), 2024
  8. TPAMI
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    Versatile Backdoor Attack with Visible, Semantic, Sample-Specific, and Compatible Triggers
    Ruotong Wang, Hongrui Chen, Zihao Zhu , Li Liu, and Baoyuan Wu
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024
  9. NeurIPS
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    BackdoorBench: A Comprehensive Benchmark of Backdoor Learning
    Baoyuan Wu, Hongrui Chen, Mingda Zhang, Zihao Zhu , Shaokui Wei, Danni Yuan, and Hongyuan Zha
    In Advances in Neural Information Processing Systems (NeurIPS), 2022
  10. ICASSP
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    From Shallow to Deep: Compositional Reasoning over Graphs for Visual Question Answering
    In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022
  11. PR
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    Cross-Modal Knowledge Reasoning for Knowledge-based Visual Question Answering
    Jing Yu, Zihao Zhu , Yujing Wang, Weifeng Zhang, Yue Hu, and Jianlong Tan
    Pattern Recognition (PR), 2020
  12. IJCAI
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    Mucko: Multi-Layer Cross-Modal Knowledge Reasoning for Fact-based Visual Question Answering
    Zihao Zhu , Jing Yu, Yujing Wang, Yajing Sun, Yue Hu, and Qi Wu
    In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2020

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