Zhaomin Wu

Research Fellow. National University of Singapore. zhaomin@nus.edu.sg

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Dr. Zhaomin Wu is a Research Fellow at the Department of Computer Science, National University of Singapore (NUS). He completed his Ph.D. in Computer Science at the National University of Singapore (NUS) in 2024 advised by Prof. Bingsheng He. He received his Bachelor’s degree from Huazhong University of Science and Technology (HUST) in 2019.

Dr. Wu’s research focuses on trustworthy machine learning, with specific interests in vertical federated learning, machine unlearning, and trustworthy large language models. His work has been recognized with awards such as the SIGMOD Honorable Mention for Best Artifact (2023), the Dean’s Graduate Research Excellence Award (NUS, 2023), an Honorable Mention for Best Ph.D. Thesis Award (NUS, 2024), and the Best Research Staff Award (NUS, 2025). His publications appear in top-tier venues including NeurIPS, ICLR, SIGMOD, ACL, EMNLP, AAAI, MLSys, and TKDE.

news

Aug 21, 2025 One paper accepted in EMNLP 2025.
May 29, 2025 I give an invited talk entitled “Towards Practical Vertical Federated Learning Systems” on behalf of Prof. Bingsheng He at the DASFAA 2025 Trust Day.
May 17, 2025 One paper accepted in ACL 2025.
Feb 25, 2025 I give an invited talkBridging Private Data Silo with Machine Learning” at the NUS Open House 2025.
Jan 12, 2025 I have received the Best Research Staff Award from Institute of Data Science, NUS.

selected publications

  1. EMNLP 2025
    Model-based Large Language Model Customization as Service
    Zhaomin Wu*, Jizhou Guo*, Junyi Hou, Bingsheng He, Lixin Fan, and Qiang Yang
    In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2025
  2. NeurIPS 2024
    Federated Transformer: Multi-Party Vertical Federated Learning on Practical Fuzzily Linked Data
    Zhaomin Wu, Junyi Hou, Yiqun Diao, and Bingsheng He
    In Advances in Neural Information Processing Systems, 2024
  3. ICLR 2024
    VertiBench: Advancing Feature Distribution Diversity in Vertical Federated Learning Benchmarks
    Zhaomin Wu, Junyi Hou, and Bingsheng He
    In The Twelfth International Conference on Learning Representations, 2024
  4. SIGMOD 2023
    DeltaBoost: Gradient Boosting Decision Trees with Efficient Machine Unlearning
    Zhaomin Wu, Junhui Zhu, Qinbin Li, and Bingsheng He
    Proc. ACM Manag. Data, 2023
  5. NeurIPS 2022
    A Coupled Design of Exploiting Record Similarity for Practical Vertical Federated Learning
    Zhaomin Wu, Qinbin Li, and Bingsheng He
    In Advances in Neural Information Processing Systems, 2022