Zhiqin (Brian) Yang

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I’m a PhD student at HKUST supervised by Prof. Yike Guo and Prof. Wei Xue I’m also working closely with Prof. Bo Han and Prof. Yonggang Zhang at the TMLR group, HKBU . Prior to this, I earned my M.S. degree from Beihang University (BUAA), advised by Prof. Hao Peng. I also completed my B.S. degree at Nanjing University of Science and Technology (NJUST), where I spent four enriching years. My research focuses on Federated Learning and its applications, particularly in privacy-preserving healthcare solutions.

Beyond academia, I am an avid basketball enthusiast and a devoted fan of Kobe Bryant. I enjoy immersing myself in live music, especially hip-hop and R&B, with Nous Underground from XAC being a favorite. Additionally, I have a deep interest in Chinese history, particularly the Ming Dynasty.

If you’re interested in discussing potential collaborations or shared passions, please feel free to reach out! I welcome diverse perspectives and ideas to broaden me. :face_holding_back_tears:

news

Feb 21, 2026 One co-first author paper on rethinking federated noisy problem got accepted by CVPR’26, congrats to all collaborators!
Feb 10, 2026 We release MemFly (got accepted by ICLR’26 workshop about MemAgent) for the agent memory workflow. Welcome to check our paper :smile:
Sep 20, 2025 Two papers about Federated Learning on Heterogeneity and Benchmarking VLM on Spatial Understanding have been accepted by NeurIPS’25. Welcome to check our paper: FedGPS, IR3D. See you in San Diego :heart_eyes:
Jun 18, 2025 We release LearnAlign to select high-quality data for LLM post-training. Welcome to check our paper:kissing_smiling_eyes:
Jul 01, 2024 I graduate from Beihang University with Outstanding Master Thesis Award:sparkles: :smile:

Selected publications

  1. NeurIPS 2023
    FedFed: Feature distillation against data heterogeneity in federated learning
    Zhiqin Yang, Yonggang Zhang, Yu Zheng, Xinmei Tian, Hao Peng, Tongliang Liu, and Bo Han
    Advances in Neural Information Processing Systems, 2023
  2. NeurIPS 2025
    FedGPS: Statistical Rectification Against Data Heterogeneity in Federated Learning
    Zhiqin Yang, Yonggang Zhang, Chenxin Li, Yiu-ming Cheung, Bo Han, and Yixuan Yuan
    Advances in Neural Information Processing Systems, 2025
  3. ICLR 2024
    Robust Training of Federated Models with Extremely Label Deficiency
    Yonggang Zhang*, Zhiqin Yang*, Xinmei Tian, Nannan Wang, Tongliang Liu, and Bo Han
    In The Twelfth International Conference on Learning Representations, 2024
  4. arXiv 2506.11480
    LearnAlign: Reasoning Data Selection for Reinforcement Learning in Large Language Models Based on Improved Gradient Alignment
    Shikun Li*, Zhiqin Yang*, Shipeng Li*, Xinghua Zhang, Gaode Chen, Xiaobo Xia, Hengyu Liu, and 1 more author
    arXiv preprint arXiv:2506.11480, 2025
  5. arXiv 2602.07885
    MemFly: On-the-Fly Memory Optimization via Information Bottleneck
    Zhenyuan Zhang, Xianzhang Jia, Zhiqin Yang, Zhenbo Song, Wei Xue, Sirui Han, and Yike Guo
    arXiv preprint arXiv:2602.07885, 2026
  6. CVPR 2026
    FedRG: Unleashing the Representation Geometry for Federated Learning with Noisy Clients
    Tian Wen*, Zhiqin Yang*, Yonggang Zhang, Xuefeng Jiang, Hao Peng, Yuwei Wang, and Bo Han
    In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, 2026

Awards

Academic Services

Journal Reviewer: Conference Reviewer: