🧐 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).
He is currently a visiting student in the PLUS Lab at ShanghaiTech under the guidance of Xuming He.
I anticipate completing my PhD by late 2025. Please feel free to contact me early.
Research Interests: Affordance learning, Multi-view Learning, Continual Learning, Active Learning, Semi-supervised Classification, Clustering.
Contact: wanxinhang@nudt.edu.cn
🔥 News
(Papers as first author are bolded.)
- 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.)
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.
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#. 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.
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.
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.
- DShield: Defending against Backdoor Attacks on Graph Neural Networks via Discrepancy Learning, Hao Yu, Chuan Ma, Xinhang Wang, 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
- 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)
- 2022.05 Member of the College Basketball Team, National University of Defense Technology.(学院篮球队队员)
- 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)
- 2018.10 Eighth place in Rope Skipping at the School sports meeting, Northeastern University. (校运会跳绳第八名)
📖 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.
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2014.09 - 2017.06, Xiangyang No.5 Middle School, Xiangyang, China.
✉ Services
- Journal Reviewer: TKDE, TCSVT, Neurocomputing.
- Conference Reviewer: ICLR(2025), NeurIPS(2024), KDD(2024, 2025), AAAI(2024, 2025), ACM MM(2023).