模式识别、机器学习、深度学习、计算机视觉、AI4Science、OCR

教育经历

2008-2013：中科院自动化所，模式识别与智能系统，博士 （导师：刘成林研究员），CCF优博
2004-2008：武汉大学，计算数学，学士，湖北省优秀学士论文

工作经历

2013至今：中国科学院自动化研究所，助理研究员，副研究员，研究员
2020至今：中国科学院大学，人工智能学院，岗位教授
2015-2016：蒙特利尔大学，国家公派访问学者，Prof. Yoshua Bengio
2012：加拿大模式识别与机器智能中心，访问学者，Prof. Ching Y. Suen

Associate Editor, IEEE Trans. Image Processing
Associate Editor, Pattern Recognition
Associate Editor, Neurocomputing
中国自动化学会模式识别与机器智能专委会，副秘书长
中国图象图形学学会文档图像分析与识别专委会，委员

2022秋季，博士生课程，《模式识别与机器学习》，中国科学院自动化所
2022秋季，研究生课程，《模式识别》，中国科学院大学（雁栖湖）
2021秋季，博士生课程，《模式识别与机器学习》，中国科学院自动化所
2021秋季，研究生课程，《模式识别》，中国科学院大学（雁栖湖）
2020秋季，博士生课程，《模式识别与机器学习》，中国科学院自动化所
2020秋季，研究生课程，《模式识别》，中国科学院大学（雁栖湖）
2019秋季，博士生课程，《模式识别与机器学习》，中国科学院自动化所
2019秋季，研究生课程，《模式识别》，中国科学院大学（雁栖湖）
2018夏季，研究生课程，《深度学习在视觉和自然语言处理中的应用》，中国科学院大学（雁栖湖）
2018秋季，博士生课程，《模式识别与机器学习》，中国科学院自动化所
2018秋季，研究生课程，《模式识别》，中国科学院大学（雁栖湖）
2017夏季，研究生课程，《深度学习在视觉和自然语言处理中的应用》，中国科学院大学（雁栖湖）
2017秋季，博士生课程，《模式识别与机器学习》，中国科学院自动化所
2017秋季，研究生课程，《模式识别》，中国科学院大学（雁栖湖）
2016夏季，研究生课程，《深度学习》，中国科学院大学（雁栖湖）

中国科学院大学“小米青年学者”，2023
科技创新2030新一代人工智能重大项目青年科学家，2022
朱李月华优秀教师奖，2021
吴文俊人工智能优秀青年奖，2020
中科院基础前沿研究计划从0到1原始创新项目，2019
中国科学院大学校级研究生优秀课程，2019
中国科学院青年创新促进会，2019
中国科协青年人才托举工程，2018 
中科院自动化所特聘青年骨干，2017
模式识别国家重点实验室优秀员工，2016
脑科学与智能技术卓越创新中心人才计划，2015
国家公派留学基金，2015
中国计算机学会优秀博士论文，2014
IEEE TPAMI焦点论文，2013

指导和协助指导学生情况：

朱飞，2023博士毕业，香港AIR中心博士后，中科院院长特别奖
李修川，2023硕士毕业，澳大利亚悉尼大学读博
徐玥，2022博士毕业，华为北京研究所高级工程师
王瑞琪，2022博士毕业，华为2012实验室
杨红明，2020博士毕业，腾讯科技大数据部门
谢龙飞，2020硕士毕业，新奥集团数字研究院
沈媛媛，2020博士毕业，北京体育大学体育工程学院讲师
何文浩，2019博士毕业，Flexiv（非夕）通用智能机器人公司
谢国森，2016博士毕业，南京理工大学教授

• Xu-Yao Zhang, Cheng-Lin Liu, Ching Y. Suen. Towards robust pattern recognition: A review. Proceedings of the IEEE, vol. 108, no. 6, pp. 894-922, June 2020.

• Xu-Yao Zhang, Guo-Sen Xie, Xiuli Li, Tao Mei, Cheng-Lin Liu. A survey on learning to reject. Proceedings of the IEEE, vol. 111, no. 2, pp. 185-215, February 2023.

• 张煦尧，刘成林，鲁棒模式识别研究进展，CAA模式识别与机器智能专委会通讯，2020年第2期：1-11，八月，2020.

• 朱飞, 张煦尧, 刘成林. 类别增量学习研究进展和性能评价. 自动化学报, 3月, 2023, 49(3): 635−660.

• Fei Zhu, Xu-Yao Zhang*, Rui-Qi Wang, Cheng-Lin Liu. Learning by seeing more classes. IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI). vol. 45, no. 6, pp. 7477-7493, June 2023.

• Hong-Ming Yang, Xu-Yao Zhang*, Fei Yin, Qing Yang, Cheng-Lin Liu. Convolutional prototype network for open set recognition. IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI), vol. 44, no. 5, pp. 2358-2370, May 2022.

• Xu-Yao Zhang, Fei Yin, Yan-Ming Zhang, Cheng-Lin Liu, Yoshua Bengio. Drawing and recognizing Chinese characters with recurrent neural network. IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI), vol. 40, no. 4, pp. 849-862, April 2018.

• Xu-Yao Zhang, Cheng-Lin Liu. Writer adaptation with style transfer mapping. IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI), vol. 35, no. 7, pp. 1773-1787, July 2013. 

• Jiao Zhang, Xu-Yao Zhang, Chuang Wang, Cheng-Lin Liu. Deep representation learning for domain generalization with information bottleneck principle, Pattern Recognition, vol. 143, article number 109737, pp. 1-12, November 2023.

• Fei Zhu, Zhen Cheng, Xu-Yao Zhang, Cheng-Lin Liu. Imitating the oracle: Towards calibrated model for class incremental learning. Neural Networks, vol. 164, pp. 38-48, July 2023.

• Zhen Cheng, Fei Zhu, Xu-Yao Zhang*, Cheng-Lin Liu. Adversarial training with distribution normalization and margin balance, Pattern Recognition, vol. 136, article number 109182, pp. 1-11, April 2023.

• Ming-Liang Zhang, Xu-Yao Zhang, Chuang Wang, Cheng-Lin Liu. Towards prior gap and representation gap for long-tailed recognition. Pattern Recognition, vol. 133, article number 109012, pp. 1-12, January 2023.

• Rui-Qi Wang, Xu-Yao Zhang, Cheng-Lin Liu. Meta-prototypical learning for domain-agnostic few-shot recognition. IEEE Trans. Neural Networks and Learning Systems (TNNLS), vol. 33, no. 11, pp. 6990-6996, November 2022

• Xiang Ao, Xu-Yao Zhang, Cheng-Lin Liu. Cross-modal prototype learning for zero-shot handwritten character recognition. Pattern Recognition, vol. 131, article number 108859, pp. 1-13, November 2022.

• Xiu-Chuan Li, Xu-Yao Zhang, Fei Yin, Cheng-Lin Liu. Decision-based adversarial attack with frequency mixup. IEEE Trans. Information Forensics and Security (TIFS), vol. 17, pp. 1038-1052, March 2022.

• Guo-Sen Xie, Xu-Yao Zhang, Yazhou Yao, Zheng Zhang, Fang Zhao, Ling Shao. VMAN: A virtual mainstay alignment network for transductive zero-shot learning. IEEE Trans. Image Processing (TIP), vol. 30, pp. 4316-4329, April 2021.

• Wenhao He, Xu-Yao Zhang, Fei Yin, Zhenbo Luo, Jean-Marc Ogier, Cheng-Lin Liu. Realtime multi-scale scene text detection with scale-based region proposal network. Pattern Recognition, vol. 98, article number 107026, pp. 1-14, February 2020.

• Xiao-Bo Jin, Xu-Yao Zhang, Kaizhu Huang, Guang-Gang Geng. Stochastic conjugate gradient algorithm with variance reduction. IEEE Trans. Neural Networks and Learning Systems (TNNLS), vol. 30, no. 5, pp. 1360-1369, May 2019.

• Wenhao He, Xu-Yao Zhang, Fei Yin, Cheng-Lin Liu. Multi-oriented and multi-lingual scene text detection with direct regression. IEEE Trans. Image Processing (TIP), vol. 27, no. 11, pp. 5406-5419, November 2018.

• Guo-Sen Xie, Xu-Yao Zhang, Shuicheng Yan, Cheng-Lin Liu. SDE: A novel selective, discriminative and equalizing feature representation for visual recognition. International Journal of Computer Vision (IJCV), vol. 124, pp. 145-168, September 2017.

• Guo-Sen Xie, Xu-Yao Zhang, Shuicheng Yan, Cheng-Lin Liu. Hybrid CNN and dictionary-based models for scene recognition and domain adaptation. IEEE Trans. Circuits and Systems for Video Technology (TCSVT), vol. 27, no. 6, pp. 1263-1274, June 2017.

• Xu-Yao Zhang, Guo-Sen Xie, Cheng-Lin Liu, Yoshua Bengio. End-to-end online writer identification with recurrent neural network. IEEE Trans. Human-Machine Systems (THMS), vol. 47, no. 2, pp. 285-292, April 2017.

• Xu-Yao Zhang, Yoshua Bengio, Cheng-Lin Liu. Online and offline handwritten Chinese character recognition: A comprehensive study and new benchmark. Pattern Recognition, vol. 61, pp. 348-360, January 2017.

• Lingfeng Wang, Xu-Yao Zhang, Chunhong Pan. MSDLSR: Margin scalable discriminative least squares regression for multicategory classification. IEEE Trans. Neural Networks and Learning Systems (TNNLS), vol. 27, no. 12, pp. 2711-2717, December 2016.

• Ming-Ke Zhou, Xu-Yao Zhang, Fei Yin, Cheng-Lin Liu. Discriminative quadratic feature learning for handwritten Chinese character recognition. Pattern Recognition, vol. 49, pp. 7-18, January 2016.

• Xu-Yao Zhang, Lingfeng Wang, Shiming Xiang, Cheng-Lin Liu. Retargeted least squares regression algorithm. IEEE Trans. Neural Networks and Learning Systems (TNNLS), vol. 26, no. 9, pp. 2206-2213, September 2015.

• Xu-Yao Zhang, Peipei Yang, Yan-Ming Zhang, Kaizhu Huang, Cheng-Lin Liu. Combination of classification and clustering results with label propagation. IEEE Signal Processing Letters, vol. 21, no. 5, pp. 610-614, May 2014.

• Xu-Yao Zhang, Cheng-Lin Liu. Evaluation of weighted Fisher criteria for large category dimensionality reduction in application to Chinese handwriting recognition. Pattern Recognition, vol. 46, no. 9, pp. 2599-2611, September 2013.

• Fei Zhu, Zhen Cheng, Xu-Yao Zhang*, Cheng-Lin Liu. OpenMix: Exploring outlier samples for misclassification detection. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Vancouver, Canada, June 18-22, 2023.

• Fei Zhu, Zhen Cheng, Xu-Yao Zhang*, Cheng-Lin Liu. Rethinking confidence reliability for failure prediction. European Conference on Computer Vision (ECCV), Tel Aviv, Israel, October 23–27, 2022. 

• Fei Zhu, Zhen Cheng, Xu-Yao Zhang, Cheng-Lin Liu. Class-incremental learning via dual augmentation.  Thirty-Fifth Conference on Neural Information Processing Systems (NeurIPS), Virtual, December 6-14, 2021.

• Fei Zhu, Xu-Yao Zhang, Chuang Wang, Fei Yin, Cheng-Lin Liu. Prototype augmentation and self-supervision for incremental learning. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Online (Nashville, United States), June 19-25, 2021.

• Wei Feng, Fei Yin, Xu-Yao Zhang, Cheng-Lin Liu. Semantic-aware video text detection. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Online (Nashville, United States), June 19-25, 2021.

• Haoru Tan, Chuang Wang, Sitong Wu, Tie-Qiang Wang, Xu-Yao Zhang, Cheng-Lin Liu. Proxy graph matching with proximal matching networks. AAAI Conference on Artificial Intelligence (AAAI), Virtual Conference, February 2-9, 2021.

• Jin-Wen Wu, Fei Yin, Yan-Ming Zhang, Xu-Yao Zhang, Cheng-Lin Liu. Graph-to-graph: Towards accurate and interpretable online handwritten mathematical expression recognition. AAAI Conference on Artificial Intelligence (AAAI), Virtual Conference, February 2-9, 2021.

• Wei Feng, Wenhao He, Fei Yin, Xu-Yao Zhang, Cheng-Lin Liu. TextDragon: A end-to-end framework for arbitrary shaped text spotting. International Conference on Computer Vision (ICCV), Seoul, Korea, October 27-November 2, 2019.

• Jin-Wen Wu, Fei Yin, Yan-Ming Zhang, Xu-Yao Zhang, Cheng-Lin Liu. Image-to-markup generation via paired adversarial learning. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), Dublin, Ireland, September 10-14, 2018.

• Hong-Ming Yang, Xu-Yao Zhang, Fei Yin, Cheng-Lin Liu. Robust classification with convolutional prototype learning. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, June 18-22, 2018.

• Wenhao He, Xu-Yao Zhang, Fei Yin, Cheng-Lin Liu. Deep direct regression for multi-oriented scene text detection. IEEE International Conference on Computer Vision (ICCV), Venice, Italy, October 22-29, 2017.

• Guo-Sen Xie, Xu-Yao Zhang, Xiangbo Shu, Shuicheng Yan, Cheng-Lin Liu. Task-driven feature pooling for image classification. IEEE International Conference on Computer Vision (ICCV), Santiago, Chile, December 13-16, 2015.

• Xu-Yao Zhang, Kaizhu Huang, Cheng-Lin Liu. Feature transformation with class conditional decorrelation. International Conference on Data Mining (ICDM), Dallas, December 7-10, 2013.

• Xu-Yao Zhang, Kaizhu Huang, Cheng-Lin Liu. Pattern field classification with style normalized transformation. International Joint Conference on Artificial Intelligence (IJCAI), Barcelona, Spain, July 16-22, 2011.

• Xu-Yao Zhang, Cheng-Lin Liu. Style transfer matrix learning for writer adaptation. IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Colorado Springs, June 21-23, 2011.