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), IEEE Transactions on Multimedia (TMM) 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.

个人简介

胡世哲，郑州大学直聘研究员，博导，IEEE/CCF Senior Member，河南省优青。主要研究具身多模态感知、可信多模态学习、信息瓶颈 (Information Bottleneck，IB) 等。已以第一/通讯作者在IEEE TPAMI、TKDE、TIP、TMM、TNNLS、TCYB、PR、EITEE、FCS、计算机学报等重要期刊及 ICLR、NeurIPS、ICML、AAAI、IJCAI、ACMMM等重要国际会议发表论文30余篇，发表后得到国内外广泛关注和积极评价。信息瓶颈IB理论综述 “A Survey on Information Bottleneck” 被顶级国际期刊IEEE TPAMI评选为 “最受欢迎文章”之一。一种多阶段多模态对比聚类算法被中国工程院院刊EITEE选为2026年第8期封面论文。担任期 IEEE Transactions on Image Processing (TIP)、IEEE Transactions on Multimedia (TMM) 和 Pattern Recognition (PR) 的副编辑 (AE)，Informatioin Fusion 和 Technologies 特刊首席客座编辑 (Leading GE), 以及会议 ICLR/ICML/AAAI/IJCAI 的领域主席 (AC) 或高级程序委员会委员 (SPC)。现任VALSE第九届执行AC、CSIG青工委委员、CCF人工智能与模式识别专委会（CCF-AI）委员、CCF计算机视觉专委会（CCF-CV）委员等。主持国自然面上/青年项目、河南省优青项目、省重大科技专项子课题等。获得荣誉包括ACM郑州分会优博奖与新星奖、省教育厅科技成果一等奖。主讲《高级语言程序设计》、《数据库系统原理》等本科课程，培养硕博生10余人。更多信息请见个人主页：https://shizhehu.github.io/.

Contact Information

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 CV and Homepage

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] [Code]

  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), 35: 8635-8647, Aug. 2026. (CCF Rank A) [PDF]

  8. [TMM] Youwei Wang, Linpu Lv, Haichuan Fang, and Shizhe Hu*: Dual-balanced Information Bottleneck for Multi-modal Information Extraction . IEEE Transactions on Multimedia (TMM), Aug. 2026. (CCF Rank A) [PDF]

  9. [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]

  10. [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]

  11. [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), 2026, 37 (8): 3727 - 3740. [PDF] (CCF Rank B)

  12. [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]

  13. [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] [Code]

  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. [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), 2027, 21 (2): 2102320. (CCF Rank T1) [PDF] [Code]

  2. [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), 27 (8): 1-13, August 2026. [PDF] [Cover Article (封面文章) in Aug. 2026] [Popular Articles in Jul. 2026] (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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