Xinhang Wan (万欣航)

Xinhang Wan (万欣航)

PRMI Lab

🧐 About Me

Xinhang Wan (万欣航) is a Ph.D student at degree College of Computer Science and Technology, National University of Defence Technology (NUDT). He is supervised by Prof. Xinwang Liu and Prof. En Zhu in Pattern Recognition & Machine Intelligence Lab (PRMI).

I anticipate completing my PhD by late 2025. Please feel free to contact me early.

Research Interests: Affordance learning, Novel class discovery, Multi-view Learning, Continual Learning, Active Learning, Semi-supervised Classification, Clustering.

Contact: wanxinhang@nudt.edu.cn

Wechat: 13390144829.

🔥 News

(Papers as first author are bolded.)

  • 2025.05:   My OMVCDR (IEEE TNNLS 2024) paper is featured as a ESI Highly Cited Paper.
  • 2025.05:   One paper has been accepted by ICML 2025 (CCF A).
  • 2025.02:   One paper has been accepted by CVPR 2025 (CCF A).
  • 2024.12:   Two papers have been accepted by AAAI 2025 (CCF A).
  • 2024.11:   I won China National Scholarship for Phd students.
  • 2024.11:   One paper has been accepted by IEEE-TNNLS (CCF B, SCI 1区).
  • 2024.09:   One paper has been accepted by NDSS 2025 (CCF A).
  • 2024.07:   One paper has been accepted by ACM MM 2024 (CCF A).
  • 2024.06:   Will talk at AI TIME.
  • 2024.05:   One paper has been accepted by IEEE-TKDE (CCF A).
  • 2024.05:   Two papers have been accepted by ICML 2024(CCF A).
  • 2024.03:   One paper has been accepted by IEEE-TIP (CCF A, SCI 1区).
  • 2024.03:   One paper has been accepted by IEEE-TNNLS (CCF B, SCI 1区).
  • 2023.07:   Two papers have been accepted by ACM MM 2023 (CCF A).
  • 2023.06:   One paper has been accepted by IEEE-TNNLS (CCF B, SCI 1区).
  • 2022.12:   One paper has been accepted by AAAI 2023 (CCF A).
  • 2022.06:   One paper has been accepted by ACM MM 2022 (CCF A).

📝 Publications

(* indicates equal contribution; # indicates corresponding authorship.)

ICML 2024
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Decouple then Classify: A Dynamic Multi-view Labeling Strategy with Shared and Specific Information

Xinhang Wan, Jiyuan Liu, Xinwang Liu#, Yi Wen, Hao Yu, Siwei Wang, Shengju Yu, Tianjiao Wan, Jun Wang, En Zhu#. Code PDF

  • We propose an efficient algorithm to tackle the sample labeling task in semi-supervised multi-view learning. The samples of low classification confidence are labeled as high priorities.
IEEE-TIP
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Fast Continual Multi-View Clustering with Incomplete Views

Xinhang Wan, Bin Xiao, Xinwang Liu#, Jiyuan Liu, Weixuan Liang, En Zhu#. Code PDF

  • We study a new paradigm for large-scale multi-view clustering called the incomplete continual data problem (ICDP) and propose FCMVC-IV to tackle the problem.
IEEE-TNNLS
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Contrastive Continual Multi-view Clustering with Filtered Structural Fusion

Xinhang Wan, Jiyuan Liu, Hao Yu, Qian Qu, Ao li, Xinwang Liu#, Ke Liang, Zhibin Dong, En Zhu#. Code PDF

  • We study a new paradigm on continual multi-view clustering, termed catastrophic forgetting problem (CFP). A clustering then sample strategy is deployed to extract and update the filtered structure information of prior views, then the attained information will guide the clustering when a new view arrives.
IEEE-TNNLS
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One-step Multi-view Clustering with Diverse Representation

Xinhang Wan, Jiyuan Liu, Xinbiao Gan, Xinwang Liu#, Siwei Wang, Yi Wen, Tianjiao Wan, En Zhu#. Code PDF

  • By directly calculating the distance among samples with diverse representation, we incorporate matrix factorization and k-means into a unified framework with linear complexity. They negotiate with each other and boost the clustering performance.
AAAI 2023 (oral)
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Auto-weighted Multi-view Clustering for Large-scale Data

Xinhang Wan, Xinwang Liu#, Jiyuan Liu, Siwei Wang, Yi Wen, Weixuan Liang, En Zhu, Zhe Liu, Lu Zhou. Code PDF

  • We remove the non-negative constraint of non-negative matrix factorization and obtain coefficient matrices with view-specific base matrices of different dimensions, then integrate them into a consensus one in a parameter-free way.
ACM MM 2022
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Continual Multi-view Clustering

Xinhang Wan, Jiyuan Liu, Weixuan Liang, Xinwang Liu#, Yi Wen, En Zhu. Code PDF

  • We propose CMVC and it is the first attempt to handle real-time issues in late fusion multi-view clustering literature and will provide an inspiration for future research.
  • Scalable Attribute-Missing Graph Clustering via Neighborhood Differentiation, Yaowenhu, Wenxuan Tu, Yue Liu, Xinhang Wan, Junyi Yan, Taichun Zhou, Xinwang Liu, ICML 2025.
  • Large-scale Multi-view Tensor Clustering with Implicit Linear Kernels, Jiyuan Liu, Xinwang Liu, Chuankun Li, Xinhang Wan, Hao Tan, Yi Zhang, Weixuan Liang, Qian Qu, Yu Feng, Renxiang Guan, Ke Liang, CVPR 2025.
  • Incremental Nyström-based Multiple Kernel Clustering, Yu Feng, Weixuan Liang, Xinhang Wan, Jiyuan Liu, Suyuan Liu, Qian Qu, Renxiang Guan, Huiying Xu, Xinwang Liu, AAAI 2025.
  • Incomplete Multi-view Clustering via Diffusion Contrastive Generation, Yuanyang Zhang, Yijie Lin, Weiqing Yan, Li Yao, Xinhang Wan, Guangyuan Li, Chao Zhang, Guanzhou Ke, Jie Xu, AAAI 2025.
  • DShield: Defending against Backdoor Attacks on Graph Neural Networks via Discrepancy Learning, Hao Yu, Chuan Ma, Xinhang Wan, Jun Wang, Tao Xiang, Meng Shen, Xinwang Liu, NDSS 2025.
  • A Lightweight Anchor-Based Incremental Framework to Multi-view Clustering, Qian Qu, Xinhang Wan, Weixuan Liang, Jiyuan Liu, Yu Feng, Huiying Xu, Xinwang Liu, En Zhu, ACM MM 2024. Code PDF
  • Multiple Kernel Clustering with Adaptive Multi-scale Partition Selection, Jun Wang, Zhenglai Li, Chang Tang#, Suyuan Liu, Xinhang Wan, Xinwang Liu#, IEEE-TKDE. Code PDF
  • Towards Resource-friendly, Extensible and Stable Incomplete Multi-view Clustering, Shengju Yu, Dong Zhibin, Siwei Wang, Xinhang Wan, Yue Liu, Weixuan Liang, Pei Zhang, Wenxuan Tu, Xinwang Liu#, ICML 2024 (spotlight). PDF
  • Scalable Incomplete Multi-View Clustering with Structure Alignment, Yi Wen, Siwei Wang#, Ke Liang, Weixuan Liang, Xinhang Wan, Xinwang Liu#, Suyuan Liu, Jiyuan Liu, and En Zhu, ACM MM 2023. Code PDF
  • Efficient Multi-View Graph Clustering with Local and Global Structure Preservation, Yi Wen*, Suyuan Liu*, Xinhang Wan, Siwei Wang, Ke Liang, Xinwang Liu#, Xihong Yang, Pei Zhang, ACM MM 2023. Code PDF
  • Unpaired Multi-View Graph Clustering with Cross-View Structure Matching, Yi Wen, Siwei Wang, Qing Liao, Weixuan Liang, Ke Liang, Xinhang Wan, Xinwang Liu#, IEEE-TNNLS.Code PDF

🎖 Honors and Awards

  • 2024.12 Outstanding Student, National University of Defense Technology. (校优秀学员，top 1%)
  • 2024.11 National scholarship, National University of Defense Technology. (研究生国家奖学金)
  • 2023.01 Outstanding Student, National University of Defense Technology. (校优秀学员，top 1%)
  • 2022.10 National scholarship, National University of Defense Technology. (研究生国家奖学金)
  • 2022.10 Fifth in the 100m at the School sports meeting, National University of Defense Technology. (校运会100m第五名)
  • 2021.06 Excellent Graduated Graduate Student of Northeastern University.(校优秀毕业生)
  • 2019.10 Outstanding CLP member, Northeastern University. (校优秀团员标兵)
  • 2018.10 Outstanding Student, Northeastern University. (校优秀学生)

📖 Educations

  • 2023.02 - now, Ph.D student, National University of Defense Technology, Changsha, China.
  • 2021.09 - 2023.01, Master, National University of Defense Technology, Changsha, China.
  • 2017.09 - 2021.06, Undergraduate, Northeastern University, Shenyang, China.

  • 2014.09 - 2017.06, Xiangyang No.5 Middle School, Xiangyang, China.

    ✉ Services

  • Journal Reviewer: TPAMI, TKDE, TNNLS, TCSVT, Neurocomputing, Pattern Recognition, Artificial Intelligence Review.
  • Conference Area Chair: IJCNN(2025)
  • Conference Reviewer: ICCV(2025), ICML(2025), CVPR(2025), ICLR(2025), NeurIPS(2024-25), KDD(2024-25), AAAI(2024-25), IJCAI(2024-25), ACM MM(2023-25), ECAI(2025).