ABOUT ME

I am an Assistant Professor in the Faculty of Computer Science and Systems Engineering at Okayama Prefectural University. I received my Ph.D. in Mathematics and Informatics from the University of Toyama. Prior to that, I received my M.S. in Software Engineering from Harbin University of Science and Technology in 2021 and my B.S. in Animal Science and Technology from Northeast Agricultural University in 2018.

RESEARCH INTEREST

Deep learning, Representation learning, Multi-view learning, etc.

Publications

Pre-prints:

Journal:

[J4] Yu Ding, Katsuya Hotta, Chunzhi Gu, Ao Li, Jun Yu, Chao Zhang. Learning to Discriminate While Contrasting: Combating False Negative Pairs with Coupled Contrastive Learning for Incomplete Multi-View Clustering. IEEE Transactions on Knowledge and Data Engineering, vol. 37, no. 10, pp. 6046-6060, 2025. [pdf]

[J3] Yu Ding, Jun Yu, Chunzhi Gu, Shangce Gao, Chao Zhang. A Multi-In and Multi-Out Dendritic Neuron Model and its Optimization. Knowledge-Based Systems, vol. 286, pp. 111442, 2024. [pdf] 

[J2] Ao Li, Yu Ding, Xunjiang Zheng, Deyun Chen, Guanglu Sun, Kezheng Lin. Bio-Inspired Structure Representation Based Cross-View Discriminative Subspace Learning via Simultaneous Local and Global Alignment. Complexity, vol. 2020, pp. 1-14, 2020. [pdf]

[J1] Ao Li, Yu Ding, Deyun Chen, Guanglu Sun, Hailong Jiang, Qidi Wu. Cross-View Feature Learning via Structures Unlocking Based on Robust Low-Rank Constraint. IEEE Access, vol. 8, pp. 46851-46860, 2020. [pdf]

Conference:

[C8] Yu Ding, Katsuya Hotta, Chunzhi Gu, Takuya Akashi, Chao Zhang. Multi-view Clustering via Self-aware Contrastive Attention Fusion. 18th International Conference on Machine Vision (ICMV), 2025.

[C7] Zi Wang, Katsuya Hotta, Yawen Zou, Yu Ding, Chao Zhang, Jun Yu. Boosting High-Resolution 3D Point Cloud Anomaly Detection with Geometric Constraints. 18th International Conference on Machine Vision (ICMV), 2025.

[C6] Yu Ding, Koichiro Kamide, Jun Yu, Chao Zhang. Dynamically Adaptive Negative Pairs for Contrastive Multi-View Clustering. 17th International Conference on Quality Control by Artificial Vision (QCAV), 2025.

[C5] Zi Wang, Katsuya Hotta, Yu Ding, Ryusuke Takada, Chao Zhang, Jun Yu. Improving Subspace Clustering by Combining Self-Expressive and Greedy Models. 17th International Conference on Quality Control by Artificial Vision (QCAV), 2025.

[C4] Daichi Kato, Yu Ding, Chao Zhang, Shogo Tokai, Chunzhi Gu. Fish Freshness Classification in Low-Light Environments via Segmentation Guidance, 17th International Conference on Knowledge and Smart Technology (KST), 2025.

[C3] Zi Wang, Yu Ding, Yawen Zou, Chao Zhang, Jun Yu. Accelerating Surrogate-Assisted Multi-Objective Evolutionary Optimization via a Dynamic Surrogate Model with Archive Updating, 17th International Conference on Knowledge and Smart Technology (KST), 2025.

[C2] Ao Li, Yu Ding, Deyun Chen, Guanglu Sun, Hailong Jiang. Discriminative Subspace Learning for Cross-view Classification with Simultaneous Local and Global Alignment. Neural Computing for Advanced Applications (NCAA), 2020.

[C1] Yu Ding, Ao Li, Kezheng Lin, Xin Liu. Joint Cross-view Heterogeneous Discriminative Subspace Learning via Low-rank Representation. 13th EAI International Conference on Mobile Multimedia Communications, (MOBIMEDIA), 2020.

Domestic Conference:

[C3] 丁宇，黄耀霆，顧淳祉，張潮，一人称視点映像に基づく論理的異常検知に関する検討, 電気学会産業応用部門大会, 2026. (NR_O)

[C2] Yu Ding, Chunzhi Gu, Chao Zhang. Reducing Redundancy for View-Decoupled Representation in Multi-View Clustering, 電気学会電子・情報・システム部門大会, OS4-2-6, 2025.

[C1] Yu Ding, Katsuya Hotta, Chunzhi Gu, Jun Yu, Chao Zhang, A Cross-View Re-Alignment Approach for Incomplete Multi-View Contrastive Clustering, 電気学会電子・情報・システム部門大会, OS4-1-4, 2024

Award:

[A1] Yu Ding, Koichiro Kamide, Jun Yu, Chao Zhang. Dynamically Adaptive Negative Pairs for Contrastive Multi-View Clustering. 15th International Conference on Quality Control by Artificial Vision (QCAV), 2025. (Best paper award)