I am currently a Postdoctoral Fellow at the University of Macau, funded by the UM Talent Program. Previously, I worked as a Postdoctoral Fellow at The Hong Kong Polytechnic University and The Hong Kong University of Science and Technology. I received my PhD from the School of Computer Science and Technology at Harbin Institute of Technology, Shenzhen. Prior to that, I obtained a bachelor’s degree in Computer Science from Jilin University and a master’s degree in Computer Science from Huazhong University of Science and Technology. My research interests include machine learning and computer vision, with a particular focus on multi-view and multimodal representation learning.

News

• 2026.04: Our paper is accepted by IEEE TMI!
• 2026.03: We are organizing a Special Issue on Trustworthy Multimodal Information Fusion for Healthcare of Information Fusion!
• 2026.01: Our paper is accepted by ICLR 2026!
• 2025.11: I received the Nomination Award for CSIG Doctoral Dissertation Incentive Program (中国图象图形学会博士学位论文激励计划提名奖)!
• 2025.11: We host a Special Issue of Electronics!
• 2025.09: Our paper is accepted by NeurIPS 2025!
• 2025.05: Our paper is accepted by ICML 2025!
• 2025.02: Our paper is accepted by IEEE TPAMI!
• 2024.05: Our paper is accepted by ICML 2024!

Publications

Conference Papers

• Permutation-Consistent Variational Encoding for Incomplete Multi-View Multi-Label Classification, Chengliang Liu, Bo Li, Bob Zhang^*, Xiaoling Luo, Yabo Liu, Jie Wen^*, ICLR 2026

• Hierarchical Information Aggregation for Incomplete Multimodal Alzheimer’s Disease Diagnosis, Chengliang Liu, Yuanxi Que, Yabo Liu, Jie Wen, Jinghua Wang, Xiaoling Luo^*, NeurIPS 2025

• Learning Compact Semantic Information for Incomplete Multi-View Missing Multi-Label Classification, Jie Wen, Yadong Liu, Zhanyan Tang, Yuting He, Yulong Chen, Mu Li, Chengliang Liu^*, ICML 2025 (Corresponding author)

• Partial Multi-View Multi-Label Classification via Semantic Invariance Learning and Prototype Modeling, Chengliang Liu, Gehui Xu, Jie Wen^*, Yabo Liu, Chao Huang, Yong Xu^*, ICML 2024

• Attention-Induced Embedding Imputation for Incomplete Multi-View Partial Multi-Label Classification, Chengliang Liu, Jinlong Jia, Jie Wen^*, Yabo Liu, Xiaoling Luo, Chao Huang, Yong Xu^*, AAAI 2024

• Masked Two-channel Decoupling Framework for Incomplete Multi-view Weak Multi-label Learning, Chengliang Liu, Jie Wen^*, Yabo Liu, Chao Huang, Zhihao Wu, Xiaoling Luo, Yong Xu^*, NeurIPS 2023

• Localized and Balanced Efficient Incomplete Multi-view Clustering, Jie Wen, Gehui Xu, Chengliang Liu^*, Lunke Fei, Chao Huang, Wei Wang^*, Yong Xu, ACM MM 2023 (Co-corresponding author)

• Highly Confident Local Structure Based Consensus Graph Learning for Incomplete Multi-view Clustering, Jie Wen^✝, Chengliang Liu^✝, Gehui Xu, Zhihao Wu, Chao Huang, Lunke Fei, Yong Xu^*, CVPR 2023 (Co-first author)

• (Oral) DICNet: Deep Instance-Level Contrastive Network for Double Incomplete Multi-View Multi-Label Classification, Chengliang Liu, Jie Wen^*, Xiaoling Luo, Chao Huang, Zhihao Wu, Yong Xu^*, AAAI 2023 (AAAI 2023 distinguished paper award)

• (Oral) Incomplete Multi-View Multi-Label Learning via Label-Guided Masked View- and Category-Aware Transformers, Chengliang Liu, Jie Wen^*, Xiaoling Luo, Yong Xu^*, AAAI 2023

• (Oral) MVCINN: Multi-View Diabetic Retinopathy Detection Using a Deep Cross-Interaction Neural Network, Xiaoling Luo^✝, Chengliang Liu^✝, Waikeung Wong, Jie Wen^*, Xiaopeng Jin , Yong Xu^*, AAAI 2023 (Co-first author)

• Pixel-Level Anomaly Detection via Uncertainty-Aware Prototypical Transformer, Chao Huang^✝, Chengliang Liu^✝, Zheng Zhang^*, Zhihao Wu, Jie Wen, Qiuping Jiang, Yong Xu^*, ACM MM 2022 (Co-first author)

Journal Papers

• Multi-view Hilbert Curve-based Hierarchical Information Aggregation for Incomplete Multimodal Alzheimer’s Disease Diagnosis, Chengliang Liu, Yuanxi Que, Wai Keung Wong, Yabo Liu, and Xiaoling Luo^*, IEEE Transactions on Medical Imaging, 2026

• Reliable Representation Learning for Incomplete Multi-View Missing Multi-Label Classification, Chengliang Liu, Jie Wen^*, Yong Xu^*, Bob Zhang, Liqiang Nie, Min Zhang, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025

• Information Recovery-Driven Deep Incomplete Multi-view Clustering Network, Chengliang Liu, Jie Wen^*, Zhihao Wu, Xiaoling Luo, Chao Huang, Yong Xu, IEEE Transactions on Neural Networks and Learning Systems, 2023

• Deep Double Incomplete Multi-View Multi-Label Learning With Incomplete Labels and Missing Views, Jie Wen, Chengliang Liu^*, Shijie Deng, Yicheng Liu, Lunke Fei, Ke Yan, Yong Xu, IEEE Transactions on Neural Networks and Learning Systems, 2023 (Corresponding author)

• Localized sparse incomplete multi-view clustering, Chengliang Liu, Zhihao Wu, Jie Wen^*, Yong Xu^*, Chao Huang, IEEE Transactions on Multimedia, 2022

• Weakly Supervised Video Anomaly Detection via Self-Guided Temporal Discriminative Transformer, Chao Huang^✝, Chengliang Liu^✝, Jie Wen, Lian Wu, Yong Xu^*, Qiuping Jiang, Yaowei Wang, IEEE Transactions on Cybernetics, 2022 (Co-first author)

Honors and Awards

• 2025.11 Nomination Award for CSIG Doctoral Dissertation Incentive Program (中国图象图形学会博士学位论文激励计划提名奖).
• 2024.11 ACM MM 2024 Outstanding reviewer.
• 2024.06 HIT Outstanding Doctoral Dissertation Award.
• 2023.10 National Scholarship of the Ministry of Education of China.
• 2023.02 AAAI 2023 distinguished paper award.

Academic Activities

• Guest Editor for a Special Issue of Information Fusion.
• Leading Guest Editor for a Special Issue of Electronics.
• Journal Reviewers of IEEE TPAMI, TNNLS, TCSVT, TMM, TKDE, TCYB, TIP.
• Senior Program Committee member of IJCAI 2025.
• Program Committee Members of AAAI, ACM MM, CVPR, ICML, NeurIPS, ICLR, ICCV.

Educations

• School of Computer Science of Technology, Harbin Institute of Technology, Shenzhen, China.
• School of Computer Science of Technology, Huazhong University of Science and Technology, Wuhan, China.
• College of Computer Science of Technology, Jilin University, Changchun, China.