About Me [Google Scholar] [Latest CV] (by Sept 2025)

Research Interests: Transfer learning/Domain adaptation, Deep learning, and Multi-view learning.

Education: Ph.D at CE, NEU, 2018; M.Eng. at CS, UESTC, 2013; B.Eng. at CS, UESTC, 2010.

Internship: Microsoft Research (with Yandong Guo and Lei Zhang), 2017; Adobe Systems Incorporated (with William Yan), 2016; Army Research Lab (with Nasser M. Nasrabadi), 2015.

Opening Positions
I am always looking for self-motivated graduate students, visiting students/scholars and postdocs. Feel free to contact me with your CV.

What is New!
[09/2025] We have 5 papers accepted by NeurIPS 2025 (4 main track and 1 benchmark track). Congratulations All!
[08/2025] We have one paper accepted by ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB 2025).
[07/2025] I accept the invitation to be an Area Chair for AAAI 2026.
[07/2025] We got two papers accepted by ACM MM 2025, one for main conference and one for benchmark. Congratulations to All.
[05/2025] We got one paper accepted by ICML 2025 and two papers accepted by IJCAI 2025. Congratulations to All.
[03/2025] I accept the invitation to be an Area Chair for NeurIPS 2025.
[01/2025] We got one paper on 3D Object Detection accepted by ICRA 2025. Congratulations to Xubin.
[12/2024] We got one paper on Source-Free Cross-Domain Segmentation accepted by AAAI 2025.
[11/2024] I accept the invitation to be an Area Chair for IJCAI 2025.
[10/2024] We got one paper on Skin Disease Diagnosis accepted by WACV 2025. Congratulations to Xin and Janet.
[09/2024] We have one paper accepted by International Journal of Human-Computer Interaction (IJHCI). Congratulations to Elahi and Taotao.
[08/2024] I accept the invitation to be an Area Chair for CVPR 2025.
[08/2024] We have one paper accepted by the MICCAI workshop ISIC Skin Image Analysis. We also received Honorable Mention Award for this work.
[07/2024] I accept the invitation to be an Area Chair for ICLR 2025.
[07/2024] We have two papers accepted by ACM Multimedia 2024.
[06/2024] Grateful to receive the grant from FY 2024-25 LAMDA Seed Funding Track 1B program.
[05/2024] We got one paper accepted by Extreme Mechanics Letters.
[03/2024] I have been appointed as Associate Editor for the IEEE Transactions on Image Processing (T-IP).
[02/2024] We got one paper accepted by CVPR 2024. Congratulations to Haifeng.

Tutorials

[T-5] Zhengming Ding, Ming Shao and Handong Zhao. Robust Multi-view Visual Learning: A Knowledge Flow Perspective, International Joint Conference on Artificial Intelligence (IJCAI-20), Yokohama, Japan
[T-4] Zhengming Ding, Hongfu Liu and Handong Zhao. Deep Multi-view Data Analytics, Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), Honolulu, Hawaii, USA
[T-3] Zhengming Ding, Ming Shao, Yun Fu. Large-Scale Multi-view Data Analysis, IEEE International Conference on Big Data, 2018, Seattle, WA, USA
[T-2] Zhengming Ding, Ming Shao, Yun Fu. Multi-view Visual Data Analytics [Slides], IEEE International Conference on Computer Vision and Pattern Recognition, 2018, Salt Lake City, USA
[T-1] Zhengming Ding, Handong Zhao, Yun Fu. Multi-view Face Representation, IEEE International Conference on Automatic Face and Gesture Recognition, 2017, Washington, DC

Selected Journal Publications [Full Journal Publications]

[J-6] Zhengming Ding, Ming Shao, and Yun Fu. Generative Zero-Shot Learning via Low-Rank Embedded Semantic Dictionary. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 41, issue. 12, pp. 2861-2874, 2019. [pdf]
[J-5] Zhengming Ding, and Yun Fu. Deep Transfer Low-Rank Coding for Cross-Domain Learning. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 30, no. 6, pp: 1768-1779, 2019. [pdf]
[J-4] Zhengming Ding, and Yun Fu. Robust Multi-view Data Analysis through Collective Low-Rank Subspace. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 29, no. 5, pp. 1986-1997, 2018. [pdf]
[J-3] Zhengming Ding, Ming Shao, and Yun Fu. Incomplete Multisource Transfer Learning. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 29, no. 2, pp. 310-323, 2018. [pdf]
[J-2] Zhengming Ding, and Yun Fu. Robust Transfer Metric Learning for Image Classification. IEEE Transactions on Image Processing (TIP), vol. 26, no.2, pp. 660-670, 2017. [pdf]
[J-1] Zhengming Ding, Ming Shao, and Yun Fu. Missing Modality Transfer Learning via Latent Low-Rank Constraint. IEEE Transactions on Image Processing (TIP), vol. 24, no. 11, pp. 4322-4334, 2015. [pdf]

Selected Conference Publications [Full Conference Publications]

[C-8] Zhengming Ding, and Hongfu Liu. Marginalized Latent Semantic Encoder for Zero-Shot Learning. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. [pdf]
[C-7] Zhengming Ding, Sheng Li, Ming Shao and Yun Fu. Graph Adaptive Knowledge Transfer for Unsupervised Domain Adaptation. European Conference on Computer Vision (ECCV), 2018 [pdf]
[C-6] Zhengming Ding, Ming Shao, and Yun Fu. Robust Multi-view Representation: A Unified Perspective from Multi-view Learning to Domain Adaption. International Joint Conference on Artificial Intelligence (IJCAI), 2018 (Survey Track) [pdf]
[C-5] Zhengming Ding, Ming Shao and Yun Fu. Low-Rank Embedded Ensemble Semantic Dictionary for Zero-Shot Learning. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. [pdf][bib][code]
[C-4] Zhengming Ding, Ming Shao and Yun Fu. Deep Robust Encoder through Locality Preserving Low-Rank Dictionary. European Conference on Computer Vision, (ECCV), 2016. [pdf]
[C-3] Zhengming Ding, Ming Shao, and Yun Fu. Deep Low-rank Coding for Transfer Learning. International Joint Conference on Artificial Intelligence (IJCAI), 2015. [pdf]
[C-2] Zhengming Ding, Yun Fu. Low-Rank Common Subspace for Multi-View Learning. IEEE International Conference on Data Mining (ICDM), 2014. [pdf]
[C-1] Zhengming Ding, Ming Shao and Yun Fu. Latent Low-Rank Transfer Subspace Learning for Missing Modality Recognition. Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI), 2014. [pdf]

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