Multi-view Representation Learning
Learning robust consensus representations from complementary and incomplete views.
Zisen Kong | 孔子森
Ph.D. Student
Institute of Information Science, Beijing Jiaotong University
Research Interests
- Multi-view Clustering and its application
- Tensor Decomposition
- Incremental Learning / Causal Inference
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👋 Hi! I received my B.S. degree from Tianjin University of Commerce in 2021. Currently, I am pursuing my Ph.D. at Beijing Jiaotong University, China, advised by Prof. Dongxia Chang. Meanwhile, I am a visiting student at the Centre for Frontier AI Research (CFAR), A*STAR, Singapore, under the co-supervision of Prof. Ivor W. Tsang and Dr. Yinghua Yao. My research advances efficient and robust learning from heterogeneous data through principled, structure-aware representation learning and information fusion.
Actively seeking collaborators!
If you are interested in my work, please feel free to contact me via email: zskong@bjtu.edu.cn.
🌍 Open Source & Community
Multi-view Benchmark Datasets Public Dataset
To facilitate research and promote cooperation within the community, we have established and made publicly available a comprehensive benchmark dataset collection covering multi-view learning. This resource library provides details and original sources of multi-view datasets, with sample sizes ranging from 124 to 152,549.
🚀 Research Thrust
An ideal learning model should: (1) capture shared and complementary information across heterogeneous views while preserving informative structures; (2) remain reliable in the presence of noise, cross-view misalignment, and uncertainty; and (3) scale efficiently to large datasets and adapt to newly arriving views. My research is dedicated to addressing the aforementioned issues.
Large-scale Anchor Learning
Building efficient anchor-based models for scalable clustering and alignment.
Tensor Methods and Optimization
Modeling high-order correlations through tensor ranks and efficient optimization.
Causal Inference and Continual Learning
Learning stable representations under causal shifts and continual updates.
🔥 News
View All📄 Publications
(* means equal contribution / # means corresponding author)
Journal Articles
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Conference Papers
🏆 Honors & Awards
View All💼 Academic Service
Conference Reviewer PC Member
NeurIPS : 2024-2025
CCF-A
CVPR: 2024–2026
CCF-A
AAAI: 2024–2027
CCF-A
ACM MM: 2025, 2026
CCF-A
ECCV: 2026
CCF-A
ICMR: 2026
CCF-B
* Served as a Program Committee (PC) or invited reviewer for the above venues.
Journal Reviewer Reviewer
Regular Reviewer for prestigious journals:
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IEEE Transactions on Image Processing (TIP)
CCF-A JCR-Q1
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IEEE Transactions on Knowledge and Data Engineering (TKDE)
CCF-A JCR-Q1
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IEEE Transactions on Multimedia (TMM)
CCF-A JCR-Q1
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IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
CCF-B JCR-Q1
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IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
CCF-B JCR-Q1
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Pattern Recognition (PR)
CCF-B JCR-Q1
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Neural Networks (NN)
CCF-B JCR-Q1
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Data Mining and Knowledge Discovery (DMKD)
CCF-B JCR-Q3
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Applied Soft Computing (ASOC)
CCF-N JCR-Q1
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Engineering Applications of Artificial Intelligence (EAAI)
CCF-C JCR-Q1
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Knowledge-Based Systems (KBS)
CCF-C JCR-Q1
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Neurocomputing
CCF-C JCR-Q2
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Pattern Recognition Letters (PRL)
CCF-C JCR-Q2
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The Journal of Supercomputing
CCF-C JCR-Q2
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Multimedia Systems (MS)
CCF-C JCR-Q2
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International Journal of Machine Learning and Cybernetics (IJMLC)
CCF-C JCR-Q3
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Discover Computing
CCF-C JCR-Q3
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Scientific Reports
CCF-N JCR-Q1
🎓 Education
Ph.D. in Information and Communication Engineering
Beijing Jiaotong University
2021 - Present
Research: Multi-view Learning, Tensor Decomposition
B.S. in Mathematics
Tianjin University of Commerce
2017 - 2021
Outstanding graduate, with training in fundamental algorithms and optimization theory.
📬 Contact
Contact Information
- zskong@bjtu.edu.cn & kongzisen@gmail.com
- No.3, Shangyuan Village, Haidian District, Beijing Jiaotong University, Beijing, China