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Welcome to Allan's Homepage [養天地正氣,法古今完人]
Zhengming (Allan) Ding

Dr. and Assistant Professor
Department of Computer Science, Tulane University
Office: 402A Stanley Thomas Hall
Postal: 6823 St. Charles Avenue, New Orleans, LA 70118, USA
Email: zding1[at]tulane[dot]edu
Fax: (504) 865-5786
About Me [Google Scholar] [Latest CV] (by Jan. 2021)

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!
[12/2020] We get one paper on zero-shot learning accepted by IEEE Transactions on Image Processing (TIP). Congratulations to Bingrong.
[12/2020] We get one paper on multi-view clustering accepted by IEEE Transactions on Image Processing (TIP).
[12/2020] We get two papers accepted by 35th AAAI Conference on Artificial Intelligence (AAAI-21) [acceptance rate: 21%].
[11/2020] I will join Department of Computer Science, Tulane University in January, 2021. Welcome to New Orleans.
[11/2020] We get two papers on Domain Adaptation accepted by WACV 2021. Congratulations to Taotao and Tongxin.
[09/2020] We get one paper on Vehicle and Person Re-Identification accepted by IEEE Transactions on Neural Networks and Learning Systems (TNNLS). Congratulations to Kai and all co-authors.
[08/2020] I will serve Senior Program Committee (SPC) for IJCAI 2021.
[08/2020] We get one paper on Endoscopic Lesions Segmentation accepted by IEEE TCSVT.
[07/2020] We get three papers accepted by ACM MM 2020 [Acceptance Rate is 27.8%]. Congratulations to Taotao for his first top-conference paper.
[07/2020] We get two papers accepted by ECCV 2020 [Acceptance Rate is 27%]. Congratulations to Haifeng and Yunyu.


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 Publications

[Full Journal Publications](5 TPAMI [IF: 19.42], 8 TNNLS [IF: 12.18], 11 TIP [IF: 9.34], etc.)

[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][bib][code]
[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][bib][code]
[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][bib][code]
[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][bib][code]
[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][bib][code]
[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][bib][code]

[Full Conference Publications] (4 CVPR, 4 ECCV, 1 ICCV, 12 AAAI, 5 IJCAI, 9 ACM MM, 4 ICDM, etc)

[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][bib][code]
[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]bib][code]
[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][bib]
[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][bib][code]
[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][bib][code]
[C-2] Zhengming Ding, Yun Fu. Low-Rank Common Subspace for Multi-View Learning. IEEE International Conference on Data Mining (ICDM), 2014. [pdf][bib][code]
[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][bib][code]