Jin Hu

Zhongguancun Laboratory & Beihang University

I am currently a PhD student (2023-) at Zhongguancun Laboratory and State Key Laboratory of Complex & Critical Software Environment (SKLCCSE), Beihang University, advised by Prof. Xianglong Liu, Prof. Ke Xu and Dr. Jiakai Wang. My current research focuses on Physical Adversarial Machine Learning and Generative Modeling, aiming to uncover the dark matter in AI systems and introduce new design paradigms for AI safety problems. I have been a Program Committee member of the 5th workshop AdvML@CVPR 2025.

Publications

  1. TPAMI 2025
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    DynamicPAE: Generating Scene-Aware Physical Adversarial Examples in Real-Time
    Jin Hu, Xianglong Liu*, Jiakai Wang, Junkai Zhang, Xianqi Yang, Haotong Qin, Yuqing Ma, and Ke Xu
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025
  2. NeurIPS 2025
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    Exploring Semantic-constrained Adversarial Example with Instruction Uncertainty Reduction
    Jin Hu, Jiakai Wang*, Linna Jing, Haolin Li, Haodong Liu, Haotong Qin, Aishan Liu, Ke Xu, and Xianglong Liu
    In Neural Information Processing Systems (NeurIPS), 2025
  3. ICASSP 2025
    Generating Targeted Universal Adversarial Perturbation against Automatic Speech Recognition via Phoneme Tailoring
    Yujun Zhang, Yanqu Chen, Jiakai Wang*, Jin Hu, Renshuai Tao, and Xianglong Liu
    In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2025
  4. IJCV submitted
    Adversarial Examples in the Physical World: A Survey
    Jiakai Wang, Xianglong Liu*, Jin Hu, Donghua Wang, Siyang Wu, Tingsong Jiang, Yuanfang Guo, Aishan Liu, and Jiantao Zhou
    CoRR, 2023
  5. Technical report
    Evaluating the practicality of learned image compression
    Hongjiu Yu, Qiancheng Sun, Jin Hu, Xingyuan Xue, Jixiang Luo, Dailan He, Yilong Li, Pengbo Wang, Yuanyuan Wang, Yaxu Dai, and others
    arXiv preprint arXiv:2207.14524, 2022