<center>Zhi Zhou</center> <center>周植</center>

Zhi Zhou
周植

Nanjing University

🤵🏻 About Me

I am a second-year Ph.D. student at the Department of Computer Science and Technology of Nanjing University advised by Professor Yu-Feng Li (李宇峰), and a member of LAMDA Group (机器学习与数据挖掘研究所), which is led by Professor Zhi-Hua Zhou (周志华).

I received my B.Sc. degree from the Department of Computer Science and Technology of Jilin University. In September 2022, I was admitted to study for a Ph.D. degree at Nanjing University without an entrance examination.

📝 Publication

Conference Papers

  • Fully Test-time Adaptation for Tabular Data.
    Zhi Zhou, Kun-Yang Yu, Lan-Zhe Guo, Yu-Feng Li.
    In: Proceedings of the 39th AAAI conference on Artificial Intelligence, Philadelphia, 2025.
    AAAI 2025. CCF-A.

  • Neuro-Symbolic Data Generation for Math Reasoning.
    Zenan Li, Zhi Zhou (co-first author), Yuan Yao, Xian Zhang, Yu-Feng Li, Chun Cao, Fan Yang, Xiaoxing Ma.
    In: Advances in Neural Information Processing Systems, Vancouver, 2024.
    NeurIPS 2024. CCF-A.

  • LSPAN: Spectrally Localized Augmentation for Graph Consistency Learning.
    Heng-Kai Zhang, Yi-Ge Zhang, Zhi Zhou, Yu-Feng Li.
    In: Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, Jeju, 2024. Page: 5462-5470.
    IJCAI 2024. CCF-A. [Paper]

  • DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection.
    Zhi Zhou, Ming Yang, Jiang-Xin Shi, Lan-Zhe Guo, Yu-Feng Li.
    In: Proceedings of the 41th International Conference on Machine Learning, Vienna, 2024.
    ICML 2024. CCF-A. [Paper] [Code] [Poster]

  • Long-tail Learning with Foundation Model: Heavy Fine-tuning Hurts.
    Jiang-Xin Shi, Tong Wei, Zhi Zhou, Jie-Jing Shao, Xin-Yan Han, Yu-Feng Li.
    In: Proceedings of the 41th International Conference on Machine Learning, Vienna, 2024.
    ICML 2024. CCF-A.

  • A Benchmark on Robust Semi-Supervised Learning in Open Environments.
    Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou, Yu-Feng Li.
    In: Proceedings of the 12th International Conference on Learning Representations, 2024.
    ICLR 2024.

  • HONGAT: Graph Attention Networks in the Presence of High-Order Neighbors.
    Heng-Kai Zhang, Yi-Ge Zhang, Zhi Zhou, Yu-Feng Li.
    In: Proceedings of the 38th AAAI conference on Artificial Intelligence, Vancouver, 2024. Page: 16750-16758.
    AAAI 2024. CCF-A.

  • Robust Test-Time Adaptation for Zero-Shot Prompt Tuning.
    Ding-Chu Zhang, Zhi Zhou (co-first author), Yu-Feng Li.
    In: Proceedings of the 38th AAAI conference on Artificial Intelligence, Vancouver, 2024. Page: 16714-16722.
    AAAI 2024. CCF-A. [Paper] [Code] [Poster] [Slide]

  • ODS: Test-Time Adaptation in the Presence of Open-World Data Shift.
    Zhi Zhou, Lan-Zhe Guo, Lin-Han Jia, Ding-Chu Zhang, Yu-Feng Li.
    In: Proceedings of the 40th International Conference on Machine Learning, Hawaii, 2023. Page: 42574-42588.
    ICML 2023. Oral Presentation. CCF-A. [Paper] [Code] [Poster] [Slide] [Video]

  • Bidirectional Adaptation for Robust Semi-Supervised Learning with Inconsistent Data Distributions.
    Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou, Jie-Jing Shao, Yu-Ke Xiang, Yu-Feng Li.
    In: Proceedings of the 40th International Conference on Machine Learning, Hawaii, 2023. Page: 14886-14901.
    ICML 2023. Oral Presentation. CCF-A. [Paper] [Code]

  • Identifying Useful Learnwares for Heterogeneous Label Spaces.
    Lan-Zhe Guo, Zhi Zhou (co-first author), Yu-Feng Li, Zhi-Hua Zhou.
    In: Proceedings of the 40th International Conference on Machine Learning, Hawaii, 2023. Page: 12122-12131.
    ICML 2023. CCF-A. [Paper] [Poster]

  • USB: A Unified Semi-supervised Learning Benchmark for Classification.
    Yi-Dong Wang, Hao Chen, Yue Fan, Wang Sun, Ran Tao, Wen-Xin Hou, Ren-Jie Wang, Lin-Yi Yang, Zhi Zhou, Lan-Zhe Guo, He-Li Qi, Zhen Wu, Yu-Feng Li, Satoshi Nakamura, Wei Ye, Marios Savvides, Bhiksha Raj, Takahiro Shinozaki, Bernt Schiele, Jin-Dong Wang, Xing Xie, Yue Zhang.
    In: Advances in Neural Information Processing Systems Datasets and Benchmarks, New Orleans, LA, 2022. Page: 3938-3961.
    NeurIPS 2022 Datasets and Benchmarks. CCF-A. [Paper] [Code]

  • STEP: Out-of-Distribution Detection in the Presence of Limited In-Distribution Labeled Data.
    Zhi Zhou, Lan-Zhe Guo, Zhan-Zhan Cheng, Yu-Feng Li, Shi-Liang Pu.
    In: Advances in Neural Information Processing Systems, Virtual Conference, 2021. Page: 29168-29180.
    NeurIPS 2021. CCF-A. [Paper] [Code] [Poster] [Slide]

  • Learning from Imbalanced and Incomplete Supervision with Its Application to Ride-Sharing Liability Judgment.
    Lan-Zhe Guo, Zhi Zhou (co-first author), Jie-Jing Shao, Yu-Feng Li, and DiDi Collaborators.
    In: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Singapore, 2021. Page: 487-495.
    KDD 2021. CCF-A. [Paper]

  • RECORD: Resource Constrained Semi-Supervised Learning under Distribution Shift.
    Lan-Zhe Guo, Zhi Zhou, and Yu-Feng Li.
    In: Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, San Diego, CA, 2020. Page: 1636-1644.
    KDD 2020. CCF-A. [Paper] [Code]

Journal Papers

  • Rts: Learning Robustly from Time Series Data with Noisy Label.
    Zhi Zhou, Yi-Xuan Jin, Yu-Feng Li.
    Frontiers of Computer Science, 18(6): 186332, 2024.
    FCS. CCF-B. [Paper] [Code]

  • LAMDA-SSL: A Comprehensive Semi-Supervised Learning Toolkit.
    Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou, Yu-Feng Li.
    Science CHINA Information Science, 67: 117101, 2024.
    SCIS. CCF-A. [Arxiv] [Code]

  • Towards Robust Test-Time Adaptation for Open-Set Recognition
    Zhi Zhou, Ding-Chu Zhang, Yu-Feng Li, Min-Ling Zhang.
    Journal of Software (软件学报), 35(4), 2024.
    JOS. CCF-A. [Paper]

Other Papers

  • You Only Submit One Image to Find the Most Suitable Generative Model
    Zhi Zhou, Lan-Zhe Guo, Pengxiao Song, Yu-Feng Li.
    NeurIPS 2023 Diffusion Workshop.
    [Page]

🛠 Software

  • LawGPT: A Large Language Model in the Legal Domain. [GitHub]
  • LAMDA-SSL: A Comprehensive and Easy-to-Use Toolkit for Semi-Supervised Learning. [GitHub]

💻 Project

  • 2022.06 - 2023.06, Fraud Detection System based on Weakly Supervised Learning, Huawei, China.
  • 2021.10 - 2022.05, Housing Sales Customer Rating Model Optimization, Beike (Internship), China.
  • 2021.03 - 2022.12, Concept Incremental Learning with Active Anotations, Hikvision, China.
  • 2020.07 - 2021.09, Liability Judgment System based on Semi-Supervised Multi-Label Learning, Didi (Internship), China.

🎖 Honor

🤝 Activity

Conference Committee

  • Senior Program Committee Member, ACML 2022.
  • Program Committee Member, NeurIPS 2022/2023/2024.
  • Program Committee Member, ICML 2022/2023/2024.
  • Program Committee Member, ICLR 2024/2025.
  • Program Committee Member, KDD 2024.
  • Program Committee Member, AAAI 2023/2024/2025.
  • Program Committee Member, ECAI 2023/2024.

Journal Reviewer

  • Reviewer for Machine Learning Journal (MLJ)
  • Reviewer for IEEE Transactions on Knowledge and Data Engineering (TKDE)
  • Reviewer for Frontiers of Computer Science (FCS)

Teaching Assistant

  • 2022.02 - 2022.06, Teaching Assistant for Introduction to Advanced Machine Learning, Nanjing Univeristy.
  • 2021.09 - 2022.01, Teaching Assistant for Introduction to Machine Learning, Nanjing Univeristy.

📖 Education

  • 2022.09 - Now, Ph.D., Computer Science and Technology, Nanjing University, Nanjing.
  • 2020.09 - 2022.06, Master, Computer Science and Technology, Nanjing University, Nanjing.
  • 2016.09 - 2020.06. Undergraduate, Tang Aoqing Honors Program (Computer Science and Technology), Jilin University, Jilin.