Shizhe Hu

Shizhe Hu

Research Fellow
PhD. Supervisor

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Shizhe Hu Shizhe Hu

Brief Bio

Dr. Shizhe Hu is currently a research fellow affiliated with the School of Computer Science and Artificial Intelligence at Zhengzhou University. He obtained the Ph.D degree of Software Engineering from Zhengzhou University in 2021, supervised by Professor Yangdong Ye. He obtained the honors of ACM Rising Star Award, ACM Zhengzhou, 2023 and ACM Outstanding Ph.D. Dissertation Award, ACM Zhengzhou, 2021.

Dr. Hu presided over five projects, including the National Natural Science Foundation of China, China Postdoctoral Science Foundation, Sub‑project​ of Henan Province Major Industrial “Challenge-Based Innovation” and Henan Province Outstanding Youth Science Fund Program.

His primary research interests focus on Information Bottleneck Theory, Multi-view/Multi-modal Learning, Trustworthy Analysis, Continual Learning, Granular Computing, Federated Learning, Clustering Analysis, Unsupervised Representation Learning, and Large Model Evaluation and Safety. He has published more than 30 papers on the TOP journals and conferences, such as IEEE TPAMI, TIP, TKDE, TNNLS, TCYB, Information Fusion, Pattern Recognition, ICLR, NeurIPS, ICML, CVPR, AAAI, IJCAI and ACM MM. In addition, He also served as the Associate Editor (AE) of IEEE Transactions on Image Processing (IEEE TIP) and Pattern Recognition (PR), and Editorial Board member of Information Processing and Management (IP&M), and also served as the Area Chair (AC) of ICLR and ICML, and Senior Program Committee (SPC) of AAAI and IJCAI-ECAI. He served as the reviewer of more than 30 international journals and conferences, including IEEE TPAMI, TNNLS, TIP, ICML, NeurIPS, AAAI, IJCAI, CVPR, ACM MM, etc. He is an IEEE Senior Member.

Please drop me a message if you have interests with me by email: ieshizhehu@zzu.edu.cn or ieshizhehu@gmail.com.

Also you can contact me with WeChat ID (微信号): hushizhe_zzu.

My Latest CV: [PDF]

DBLP: [DBLP]
Google Scholar: [Google Scholar]

Representative Work

(# denotes co-first author, * denotes the corresponding author)

Journals

  1. [TPAMI] Shizhe Hu, Zhengzheng Lou, Xiaoqiang Yan, and Yangdong Ye*: A Survey on Information Bottleneck . IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 46(8): 5325-5344, Aug. 2024. (CCF Rank A) [PDF] [Poster_ChineseVersion] [Github] [Popular Articles in Jul. 2024]

  2. [TKDE] Shizhe Hu, Xiaoqiang Yan, Yangdong Ye*: Multi-task Image Clustering through Correlation Propagation. IEEE Transactions on Knowledge and Data Engineering (TKDE) . 33(3): 1113-1127, Mar. 2021. (CCF Rank A) [PDF]

  3. [TIP] Shizhe Hu, Zhengzheng Lou, and Yangdong Ye*: View-wise Versus Cluster-wise Weight: Which Is Better for Multi-view Clustering?. IEEE Transactions on Image Processing (TIP) 31: 58-71, Jan. 2022. (CCF Rank A) [PDF]

  4. [TIP] Chaoyang Zhang, Zhengzheng Lou, Qinglei Zhou, and Shizhe Hu*: Multi-View Clustering via Triplex Information Maximization. IEEE Transactions on Image Processing (TIP), 32: 4299-4313, Jul. 2023. (CCF Rank A) [PDF]

  5. [TIP] Zhengzheng Lou, Hang Xue, Yanzheng Wang, Chaoyang Zhang, Xin Yang, and Shizhe Hu*: Parameter-free Deep Multi-modal Clustering with Reliable Contrastive Learning . IEEE Transactions on Image Processing (TIP), 34: 2628-2640, Apr. 2025. (CCF Rank A) [PDF]

  6. [TIP] Zhengzheng Lou, Mingyang Lv, Yuhan Zhan, Yingxuan Li, Chaoyang Zhang, and Shizhe Hu*: Granular Information Bottleneck for Deep Multi-modal Clustering. IEEE Transactions on Image Processing (TIP), 35: 7307-7318, Jul. 2026. (CCF Rank A) [PDF]

  7. [TIP] Shizhe Hu, Jiahao Fan, Yucong Wu, Jinlan Wang, Xiaoheng Jiang, Pei Lv, Mingliang Xu*: To the Best of Trust: Full-Stage Trusted Multi-modal Clustering . IEEE Transactions on Image Processing (TIP), Accepted, Aug. 2026. (CCF Rank A)

  8. [TNNLS] Shizhe Hu, Zenglin Shi, Xiaoqiang Yan, Zhengzheng Lou, and Yangdong Ye*: Multiview Clustering with Propagating Information Bottleneck. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 35(7): 9915-9929, Jul. 2024. (CCF Rank B) [PDF]

  9. [TNNLS] Shizhe Hu, Chengkun Zhang, Guoliang Zou, Zhengzheng Lou, and Yangdong Ye*: Deep Multiview Clustering by Pseudo-label Guided Contrastive Learning and Dual Correlation Learning . IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 36(2): 3646-3658, Feb. 2025. (CCF Rank B) [PDF] [Code]

  10. [TNNLS] Zhengzheng Lou, Yucong Wu, Ke Zhang, Chaoyang Zhang, Bo Ji, and Shizhe Hu*: Structure-enhanced Self-supervised Weighted Information Bottleneck for Multiview Clustering . IEEE Transactions on Neural Networks and Learning Systems (TNNLS), Accepted, Jan. 2026. [PDF] (CCF Rank B)

  11. [TCYB] Shizhe Hu, Zenglin Shi, Yangdong Ye*: DMIB: Dual-correlated Multivariate Information Bottleneck for Multi-view Clustering. IEEE Transactions on Cybernetics (TCYB) 52(6): 4260-4274, Jun. 2022. (CCF Rank B) [PDF]

  12. [IPM] Shizhe Hu, Guoliang Zou, Chaoyang Zhang, Zhengzheng Lou, Ruilin Geng, and Yangdong Ye*: Joint Contrastive Triple-learning for Deep Multi-view Clustering. Information Processing and Management (IPM), 60(3):103284, May. 2023. (CCF Rank B) [PDF] [Code] [Highly Cited Paper]

Conferences

  1. [ICLR'26] Shizhe Hu, Zhangwen Gou, Shuaiju Li, Jin Qin, Xiaoheng Jiang, Pei Lv, Mingliang Xu*: Calibrated Information Bottleneck for Trusted Multi-modal Clustering . In International Conference on Learning Representations (ICLR) 2026. (CCF Rank A) [PDF]

  2. [NeurIPS'25] Yanzheng Wang#, Xin Yang#, Yujun Wang, Shizhe Hu*, Mingliang Xu*: Diversity-oriented Deep Multi-modal Clustering. Annual Conference on Neural Information Processing Systems (NeurIPS), Accepted, Dec. 2025. (CCF Rank A) [PDF]

  3. [ICML'26] Zhengzheng Lou, Yuhan Zhan, Mingyang Lv, Yingxuan Li, Yuyang Du, Shizhe Hu*: Structure-aware Granular-Ball based Information Bottleneck for Multi-modal Clustering . Forty-third International Conference on Machine Learning (ICML), Seoul, South Korea, July 6th - 11th, 2026. (CCF Rank A) [PDF]

  4. [ICML'25] Zhengzheng Lou, Hang Xue, Chaoyang Zhang, Shizhe Hu*: A Peer-review Look on Multi-modal Clustering: An Information Bottleneck Realization Method. Forty-second International Conference on Machine Learning (ICML), May. 2025. (CCF Rank A) [PDF]

  5. [ICML'25] Zhengzheng Lou, Ke Zhang, Yucong Wu, Shizhe Hu*: Super Deep Contrastive Information Bottleneck for Multi-modal Clustering. Forty-second International Conference on Machine Learning (ICML), May. 2025. (CCF Rank A) [PDF] [Code]

  6. [AAAI'26] Guoliang Zou#, Tongji Chen#, Sijia Li, Jin Qin, Yangdong Ye*, Shizhe Hu*: Interest-driven Deep Multi-modal Clustering. AAAI Conference on Artificial Intelligence (AAAI) 2026. [Oral] (CCF Rank A) [PDF]

  7. [AAAI'25] Shizhe Hu, Jiahao Fan, Guoliang Zou*, Yangdong Ye*: Multi-aspect Self-guided Deep Information Bottleneck for Multi-modal Clustering. AAAI Conference on Artificial Intelligence (AAAI), 39(16), 17314-17322, April. 2025. (CCF Rank A) [PDF] [Code]

  8. [AAAI'25] Shizhe Hu, Binyan Tian, Weibo Liu, Yangdong Ye*: Self-supervised Trusted Contrastive Multi-view Clustering with Uncertainty Refined. AAAI Conference on Artificial Intelligence (AAAI), 39(16), 17305-17313, April. 2025.(CCF Rank A) [PDF] [Code]

  9. [ACM MM'26] Guoliang Zou#, Sijia Li#, Jinlan Wang, Tianyi Zhang, Pantongtong Li, Yangdong Ye*, Shizhe Hu*: Proxy Information Bottleneck for Multi-modal Clustering. ACM Multimedia (ACM MM), Rio de Janeiro, Brazil, 10–14 Nov. 2026. (CCF Rank A)

  10. [ACM MM'24] Guoliang Zou#, Yangdong Ye#, Tongji Chen, Shizhe Hu*: Learning Dual Enhanced Representation for Contrastive Multi-view Clustering. ACM Multimedia (ACM MM), Oct. 2024. (CCF Rank A) [PDF] [Code]

  11. [ACM MM'22] Shizhe Hu, Ruilin Geng, Zhaoxu Cheng, Chaoyang Zhang, Guoliang Zou, Zhengzheng Lou, Yangdong Ye*: A Parameter-free Multi-view Information Bottleneck Clustering Method by Cross-view Weighting. ACM MM Oct. 2022. (CCF Rank A) [PDF] [PPT] [Poster] [Video Presentation]

Chinese Scientific Journals

  1. [EITEE] Yanzheng Wang#, Yujun Wang#, Fengshuo Dai, Xin Yang, Xiaoheng Jiang, Pei Lv, Shizhe Hu*, Mingliang Xu*: Multi-stage Contrastive Multi-modal Clustering with Consistency Retained . ENGINEERING Information Technology & Electronic Engineering (EITEE), Accepted, Jun. 2026. [PDF] (CCF Rank T1)

  2. [FCS] Shizhe Hu, Jinlan Wang, Jiahao Fan, Sijia Li, Jin Qin, Xiaoheng Jiang, Pei Lv, and Mingliang Xu*: Relational Contrastive Multi-view Clustering. Frontiers of Computer Science (FCS), Accepted, Jan. 2026. [PDF] (CCF Rank T1)

  3. [计算机工程] 姜晓恒, 孙柯凡, 邵蒙恩, 胡世哲*, 徐明亮: 联合类对抗学习和动态融合的可信多模态分类 . 计算机工程. 2026. [PDF] (CCF Rank T2)

  4. [计算机学报] 胡世哲, 娄铮铮，王若彬，闫小强，叶阳东*: 一种双重加权的多视角聚类方法 . 计算机学报. 43(9), 1708-1720, Sep. 2020. [PDF] (CCF Rank T1)

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