非线性优化理论与算法，机器学习，大规模数据处理，模式识别

070105-运筹学与控制论

2003.03--2008.10   上海交通大学   博士

2024.09--至今              中国科学院大学  长聘教授 

2018.12--2024.09        中国科学院大学   教授 

2013.06--2018.11        中国科学院大学   副教授 

2010.09--2012.06        中国科学院大学   博士后 

1996.07--2012.04        山东科技大学       副教授

矩阵论
现代智能优化方法
人工智能数学基础
智能优化方法
机器学习中的优化模型和算法
生物数学
生物统计与实验设计
Matlab在科学计算中的应用
数值计算方法

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（ 1 ） 基于信息瓶颈理论的解纠缠表征学习方法及装置, 发明专利, 2023, 第 1 作者, 专利号: 202310195436.X

（ 2 ） 一种指纹图像重构方法、指纹图像特征提取方法及装置, 发明专利, 2021, 第 1 作者, 专利号: CN113313627A

(1)《基于多种生物特征相结合的身份认证模组关键技术研究》，中国运筹学会科学技术奖运筹应用奖，排名第一位，2022.12

(2) Optimization Models and Algorithms for Fingerprint Recognition and Its Application in AFIS of China, 二等奖, 排名第二位, 2017

(3)《指纹自动识别系统》中国运筹学会科学技术奖运筹应用奖, 排名第三位，2016

2025年度

1. Xin Sun, Tiande Guo, Congying Han*, Hongyang Zhang.  Greedy algorithms for stochastic monotone k-submodular maximization under full-bandit feedback， Journal of Combinatorial Optimization (2025) 49:7.

2. Shichen Liao, Yan Liu, Congying Han∗, Tiande Guo. Momentum-based variance-reduced stochastic Bregman proximal gradient methods for nonconvex nonsmooth optimization Expert Systems with Applications, (2025) 125960.

3.Bonan Li, Zicheng Zhang, Xuecheng Nie, Congying Han*,Yinhan Hu, Xinmin Qiu, Tiande Guo. StyO: Stylize Your Face in Only One-Shot, AAAI2025.

2024年度

1.Ziwen Liu , Mingqiang Li, Congying Han* , Siqi Tang, and Tiande Guo STDNet: Rethinking Disentanglement Learning with Information Theory. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, VOL. 35, NO. 8, AUGUST 2024, 10407-10421

2.Yudong Hu, Congying Han*, Tiande Guo, Hao Xiao. Applying Opponent Modeling for Automatic Bidding in Online Repeated Auctions. AAMAS '24: 843–851.

3.Anqi Li, Tiande Guo, Congying Han*, Bonan Li, Haoran Li. On the optimal pivot path of simplex method for linear programming based on reinforcement learning. SCIENCE CHINA Mathematics. Special Issue on AI Methods for Optimization Problems. June 2024 Vol. 67 No. 6: 1263-1286.

4.Yuchen Shi, Congying Han & Tiande Guo∗. NeuroPrim: An attention-based model for solving NP-hard spanning tree problems, SCIENCE CHINA Mathematics. Special Issue on AI Methods for Optimization Problems. June 2024 Vol. 67 No. 6: 1359-1376.

5.Shichen Liao, Congying Han*, Tiande Guo, Bonan Li。Subspace Newton method for sparse group l0 optimization Problem, Journal of Global Optimization (2024) 90:93–125. https://doi.org/10.1007/s10898-024-01396-y

6.Zicheng Zhang, Ruobing Zheng, Bonan Li, Congying Han*, Tianqi Li,Meng Wang, Tiande Guo,etl. Learning Dynamic Tetrahedra for High-Quality Talking Head Synthesis. CVPR 2024: 5209-5219

7.Haoran Li, Zicheng Zhang, Wang Luo, Congying Han*，Yudong Hu， Tiande Guo  Shichen Liao. Towards Optimal Adversarial Robust Q-learning with Bellman Infinity-error, ICML 2024, PMLR (Proceedings of Machine Learning Research) 235:29324-29372.（Oral)

8.Xinmin Qiu, Congying Han, Zicheng Zhang, Bonan Li*, Tiande Guo1, Pingyu Wang, and Xuecheng Nie. BlazeBVD: Make Scale-Time Equalization Great Again for Blind Video Deflickering, ECCV2024, Lecture Notes in Computer Science, 15075: Pages:37-53.

9.Wenzhao Liu, Congying Han*, Tiande Guo, Haoran Li, Zicheng Zhang. Fusion of Multi-level Information: Solve Large-scale Traveling Salesman Problem with an Efficient Framework. 31st International Conference on Neural Information Processing (ICONIP 2024).

2023年度

1.Tian-De Guo, Yan Liu*, Cong-Ying Han. An Overview of Stochastic Quasi-Newton Methods for Large-Scale Machine Learning, Journal of the Operations Research Society of China (2023) 11:245–275

2.Bonan Li, Yinhan Hu, Xuecheng Nie, Congying Han*, Xiangjian Jiang, Tiande Guo, Luoqi Liu. DropKey for Vision Transformer, CVPR 2023，Pages：22700-22709.

3.Zicheng Zhang, Yinglu Liu, Congying Han*, Yingwei Pan, Tiandeguo, Ting Yao.  Transforming Radiance Field with Lipschitz Network for Photorealistic 3D Scene Stylization, CVPR2023, Pages:20712-20721. （highlight）.

4.Weichen Zhao, Tiande Guo, Xiaoxi Yu, Congying Han*. A Learnable Sampling Method for Scalable Graph Neural Networks, Neural Networks，162（2023）412-424 .

5.Ziwen Liu, Chenguang Wang, Congying Han*, Tiande Guo. Learning graph representation by aggregating subgraphs via mutual information maximization. Neurocomputing, 548 (2023) 126392.

6.Xinmin Qiu, Congying Han, Zicheng Zhang, Bonan Li*, Tiande Guo, Xuecheng Nie. DiffBFR: Bootstrapping Diffusion Model for Blind Face Restoration, MM ’23, October 29-November 3, 2023, Ottawa, ON, Canada. 2023.

7.Zicheng Zhang, Bonan Li,  Xuecheng Nie, Congying Han†,  Tiande Guo,  Luoqi Liu. Towards Consistent Video Editing with Text-to-Image Diffusion Models. 37th Conference on Neural Information Processing Systems (NeurIPS 2023). Advances in Neural Information Processing Systems, 36: 58508-58519.

8.Chenguang Wang, Congying Han*,Tiande Guo，Man Ding.  Solving uncapacitated P-Median problem with reinforcement learning assisted by graph attention networks, Applied Intelligence. 2023,53 (2) : 2010-2025

9.Yudong Hu, Congying Han*, Haoran Li, Tiande Guo. Modeling Opponent Learning in Multiagent Repeated Games, Applied Intelligence, 2023, 53 (13) : 17194-17210

10.Anqi Li, Congying Han*, Tiande Guo, Bonan Li. Generating linear programming instances with controllable rank and condition number, Computers and Operations Research, 162(2024)106471.

11.LIU Yonghong, HAN Congying*, GUO Tiande. Fingerprint orientation field estimation algorithm based on deep learning. Operations Research Transactions（中文）, 2023, 27(4): 1-19.

2022年度

1.Bonan Li, Pengfei Xiong, Congying Han*, Tiande Guo. Shrinking Temporal Attention in Transformers for Video Action Recognition, The Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI-22)，Pages: 1263-1271.

2.Zicheng Zhang, Yinglu Liu, Congying Han*, Hailin Shi, Tiande Guo, Bowen Zhou. PetsGAN: Rethinking Priors for Single Image Generation，The Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI-22)，Pages:3408-3416.(Oral)

3.Jia Hu, Congying Han*, Tiande Guo，Tong Zhano. On inexact stochastic splitting methods for a class of nonconvex composite optimization problems with relative error, Optimization Methods and Software, 2022, 1-33.

4.Chenguang Wang, Yaodong Yang, Oliver Slumbers, Congying Han†, Tiande Guo, Haifeng Zhang3, Jun Wang. A Game-Theoretic Approach for Impoving Generalization Ability of TSP Solvers, ICLR Workshop on Gamification and Multiagent Solutions, 2022.

5.Zicheng Zhang, Yinglu Liu, Congying Han*, Tiande Guo, Ting Yao, Tao Mei. Generalized One-shot Domain Adaptation of Generative Adversarial Networks, The 36th Conference on Neural Information Processing Systems(NeurIPS 2022), 35:13718--13730

2021年度

1. Zhou, Bc., Han, Cy*. & Guo, Td. Convergence of Stochastic Gradient Descent in Deep Neural Network.  Acta Math. Appl. Sin. Engl. Ser. 37, 126–136 (2021). https://doi.org/10.1007/s10255-021-0991-2

2. Bonan Li，Congying Han*，Tiande Guo，Tong Zhao. Disentangled features with direct sum decomposition for zero shot learning. Neurocomputing, 426: 216-226. https://doi.org/10.1016/j.neucom.2020.09.065

2020年度

1.Min Wu, Congying Han*, Tiande Guo, et al. Registration and matching method for directed point set with orientation attributes and local information, Computer Vision and Image Understanding, 191(2020)102866

2.Baicun Zhou, Congying Han*, Yonghong Liu Tiande Guo et al. Fast Minutiae Extractor Using Neural Network. Pattern Recognition. Pattern Recognition, 103 (2020) 107273

3.郭田德 , 韩丛英*. 人工智能机理解释与数学方法探讨. 中国科学: 数学, 50(11):1541-1578, 2020.

4.Siqi Tang, Congying Han*,Tiande Guo. Point matching algorithm based on machine learning method, Journal of University of Chinese Academy of Sciences(中国科学院大学学报), 37(4): 450-457, 2020.

2019年度

1.专著：组合优化机器学习方法.郭田德 韩丛英 唐思琦. 科学出版社 北京 2019年11月，第一版。

2.郭田德, 韩丛英*, 李明强. 逐层数据再表达的前后端融合学习的理论及其模型和算法, 中国科学: 信息科学 49(6), 739-759 (2019).

3.Yonghong Liu, Baicun Zhou, Congying Han*, Tiande Guo & Jin Qin. A novel method based on deep learning for aligned fingerprints matching, Applied Intelligence. DOI 10.1007/s10489-019-01530-4. 2019. 

4.郭田德, 韩丛英*. 从数值最优化方法到学习最优化方法. 运筹学学报, 23（4）:1-12(2019).

5.Tiande Guo, Congying Han*, Siqi Tang, and Man D. Solving Combinatorial Problems with Machine Learning Methods, 207-229. © Springer Nature Switzerland AG 2019 D.-Z. Du et al. (eds.), Nonlinear Combinatorial Optimization, Springer Optimization and Its Applications 147, https://doi.org/10.1007/978-3-030-16194-1_9 丛书的一章

6.Li Sun,Congying Han, and Ziwen Liu. Active Set Type Algorithms for Nonnegative Matrix Factorization in Hyperspectral Unmixing, Mathematical Problems in Engineering, Volume 2019, Article ID 9609302, 10 pages. https://doi.org/10.1155/2019/9609302 online. 

2018年度

1.李明强, 韩丛英*, 郭田德. 新的梯度算法求解单位球笛卡尔积约束优化问题，应用数学学报，2018 Vol. 41 (1): 43-54. 2018年1月。

 2.Li Mingqiang Guo Tiande and Han Congying*. New project gradient method for quadratic programming with linear equality constraints. Journal of University of Chinese Academy of Sciences(中国科学院大学学报)，Vol 35, No. 3,2018年5月，289-296.

 3.Yonghong Liu  , Baicun Zhou , Congying Han *, Tiande Guo and Jin Qin ，A Method for Singular Points Detection Based on Faster-RCNN. Applied Sciences, 1-11. Online. Appl. Sci. 2018, 8, 1853;  doi:10.3390/app8101853

2017年度

1. 郭田德，韩丛英*，赵彤，阿勇，吴敏，白超超，唐思琦. 大库容量指纹自动识别系统中的优化模型与算法，运筹学学报，2017年12月，21（4）：19-33，DOI: 10.15960/j.cnki.issn.1007-6093.2017.04.001,ISSN: 1007-6093

2.Mingqiang Li , Congying Han*，Ruxin Wang，Tiande Guo. Shrinking gradient descent algorithms for totalvariation regularized image denoising.  Comput Optim Appl (2017) 68（3）:643–660 ,2017年7月，DOI 10.1007/s10589-017-9931-8.ISSN: 0926-6003

3.Siqi Tang, Jin Qin, Yan Liu, Congying Han*， Tiande Guo.  An Efficient Slap Fingerprint SegmentationAlgorithm Based on Convnets and Knuckle Line. J. Zhou et al. (Eds.): CCBR （Chinese Conference on Biometric Recognition）2017, LNCS 10568, pp. 231–239, 2017.https://doi.org/10.1007/978-3-319-69923-3_25, 会议2017.10.28-29，深圳，中国，Springer International Publishing AG 2017 .

4.Jin Qin, Congying Han*, Chaochao Bai, Tiande Guo. Multi-Scaling Detection of Singular PointsBased on Fully Convolutional Networks inFingerprint Images. J. Zhou et al. (Eds.): CCBR （Chinese Conference on Biometric Recognition）2017, LNCS 10568, pp. 221–230, 2017.https://doi.org/10.1007/978-3-319-69923-3_24, 会议2017.10.28-29，深圳，中国，Springer International Publishing AG 2017 .

5.Jin Qin, Siqi Tang, Congying Han*, Tiande Guo. Partial Fingerprint Identification Algorithm Based-on the Modified Generalized Hough Transform on Mobile Device. Ninth InternationaI Conference on Graphic and Image Processing(ICGIP)，2017，10615Z1-10615Z-10. 

6. Jin Qin, Siqi Tang, Congying Han*, and Tiande Guo. Partial Fingerprint Matching via Phase-only Correlation and Deep Convolutional Neural Network. ICONIP Springer International Publishing AG 2017.D. Liu et al. (Eds.): ICONIP 2017(The  24th International Conference On Neural Information Processing), Part VI, LNCS 10639, pp. 602–611, 2017.https://doi.org/10.1007/978-3-319-70136-3_64，广州，11月14-18.

2016年度

1.LIU Xiao, GUO Tiande, HAN Congying*, LI mingqiang. Super resolution reconstruction of single image with denoising and upscaleing, Journal of University of Chinese Academy of Sciences. 33(5):596-603, 2016

2.Ruxin Wang, Congying Han*, Tiande Guo. A Novel Fingerprint Classification Method Based on Deep Learning, 2016 23rd International Conference on Pattern Recognition (ICPR), Cancún Center, Cancún, México, December 4-8, 2016, 931-936

3.Ruxin Wang, Congying Han*, Mingqiang Li, Tiande Guo. Single Image Super-Resolution Reconstruction Based on Edge-Preserving with External and Internal Gradient Prior Knowledge, ACCV (Asian Conference on Computer Vision) 2016 Workshops , Part I, LNCS 10116, 191-205,2017. DOI: 10.1007/978-3-319-54407-6_13. Nov 21, 2016 - Nov 23, 2016, Taipei, Taiwan

2015年度

1.Xiao Liu, Congying Han*, Tiande Guo，A Robust Point Sets Matching Method，Advances in Swarm and Computational Intelligence.Vol. 9142, Lecture Notes in Computer Science, pp 383-390

2014年度
1. Hongwei REN , Congying HAN（通讯作者），Tiande Guo, Wei PEI , Energy Losses and Voltage Stability Study in Distribution Network with Distributed Generation, Journal of Applied Mathematics, Vol. 2014, ID 939482, pp.1-7,2014. Http://dx.doi.org/10.1155/2014/939482. Hindawi Publishing Corporation.(SCI) 
2. Cong-ying HAN, Fang-ying ZHENG, Tian-de GUO, Guo-ping HE, Parallel Algorithms for Large-scale Linearly Constrained Minimization Problem. Acta Mathematicae Applicatae Sinica, English Series. Vol. 30, No.3 (2014), 1-14. DOI: 10.1007/s10255-013-0300-9.(SCI)

2013年度
1. Congying Han,Mingqiang Li, Tong Zhao, and Tiande Guo. An Accelerated Proximal Gradient Algorithm for Singly Linearly Constrained Quadratic Programs with Box Constraints,The Scientific World Journal ,Volume 2013 (2013), Article ID 246596, pp.1-6，http://dx.doi.org/10.1155/2013/246596，ISSN: 1537-744X, Research Article. (SCI)
2. R. Kong, C. Han, T. Guo and W. Pei, "An Energy-Based Centrality for Electrical Networks," Energy and Power Engineering, ISSN：1949-243X, eIssN:1947-3818, Vol. 5 No. 4B, 2013, pp. 597-602. doi: 10.4236/epe.2013.54B115.
3. 任洪伟，韩丛英，裴玮，郭田德. "基于多目标优化模型的分布式电源选址方案研究",电力系统保护与控制，Vol. 41，No. 24, 2013年12月16日,64-69.
4. 王永丽, 韩丛英(通讯作者), 李田,李明强. 求解不等式约束优化问题严格互补松弛条件的QP-Free新算法, 应用数学学报, 36(1), 1-13, 2013.
5. Congying Han,Tingting Feng, Guoping He, and Tiande Guo. Parallel Variable Distribution Algorithm for Constrained Optimization with Nonmonotone Technique, Journal of Applied athematics,Vol. (2013), Article ID 295147, 1-7.(SCI) 
6. 张学成, 韩丛英, 赵彤, 杨海珍. 基于秩和模型的大型科学仪器利用评价研究， 2013 34 (4): 108-114. 科研管理 ISSN 1000-2995.
7. Congying Han, Guangqi Shao, Yang Hao, Yong A, Tiande Guo. Non-negative Matrix Factorization Based On Locally Linear Embedding, 2013 ISORA 978-1-84919-713-7 , IET,138-141.
8.Yang Hao, Congying Han(通讯作者), Guangqi Shao, and Tiande Guo. Generalized Graph Regularized Non-negative Matrix Factorization for Data Representation, Proceedings of the 2012 International Conference on Information Technology and Software Engineering, Lecture Notes in Electrical Engineering Vol. 210, 2013, 1-12.

2012年度
1. Guangqi Shao, Congying Han, Tiande Guo, and Yang Hao. An NMF-Based Method for the Fingerprint Orientation Field Estimation. Computer and Information Science 2012，Studies in Computational Intelligence, Vol. 429, 2012, 93-104.

2011年度
1. Fangying Zheng, Congying Han(通讯作者), Yongli Wang. Parallel SSLE Algorithm for Large Scale Constrained Optimization. Applied Mathematics and Computation, 2011, 217(12): 5377-5384. (SCI & EI).
2. Liang Fang, Congying Han. A New One-step Smoothing Newton Method for the Second- order Cone Complementarity Problem. Mathematical Methods in the Applied Sciences, 2011, 34(3): 347-359.(SCI) 
3. 冯婷婷,韩丛英(通讯作者),贺国平. 修正的SQP型并行变量分配算法，数学物理学报, 2011,31A(6). 
4. 李晓蕊,韩丛英,贺国平. 求解MINLP的几类罚函数方法的分析和探讨. 数学实践与认识, 2011，41(1):202-208.
5. 徐晓,韩丛英,张永建,张永超. 基于最佳一致逼近理论求解矿用通风机性能曲线，煤炭学报，2011,Vol. 36(S. 1),186-190.(EI) 

2010年度之前部分
1. Li Xiaorui, Han Congying, He Guoping. A Parallel Algorithm for SVM Based on Extended Saddle Point Condition. Communications in Computer and Information Science(CCIS), 2010, 105(1):129-136(EI).
2. Rong Hua,Congying Han(通讯作者), Guoping He. Parallel Pattern Search Method for Optimization Problem with Bounded Constraints. International Conference on Computational Intelligence and Industrial Application (PACIIA 2010), 2010, 6:345-348.
3.黄利国, 韩丛英, 孙莉. 基于变量转换的并行优化算法. 计算机工程, 2010, 36(23):34-35.
4. Congying Han, Yongli Wang, Guoping He. On the Convergence of Asynchronous Parallel Algorithm for Large-Scale Linearly Constrained Minimization Problem. Applied Mathematics and Computation, 2009, 211(2):434-441 (SCI&EI ).
5. Congying Han, Lijun Xu, Guoping He. Mining Recent Frequent Itemsets in Sliding Windows over Data Streams. Computing and Informatics, 2008, 27(3):315-339(SCI). 6. Han Congying, He Guoping, Duan Hua, Zhang Xuping. A Binding Number Computation of Graph. Fuzzy Systems and Knowledge Discovery, 2008, 4: 285-288, 18-20 (EI).
7. Han Congying, He Guoping, Zhang Xuping, Cui Huanqing. Distributed Parallel Algorithm For Nonlinear Optimization Without Derivatives，SNPD 2007:Eighth ACIS International Conference on Software Engineering，Artificial Intelligence，Networking and Parallel/Distributed Computing, 2007, 2: 512-515 (EI).

（1） 组合优化机器学习方法, 中国科学出版社, 2019-11, 第 2 作者

1. 组合优化问题的类学习算法研究，国家自然科学基金重点项目，负责人，193万，国家任务，202501-202912

2. 强化学习的数学理论与随机优化的自学习方法, 科技部重点研发项目，子课题负责人，105万，国家任务, 202212-202711

3. 信息驱动的系统认知与博弈演化学习方法研究，科技部重点研发项目，课题负责人, 450万，国家任务, 202112-202611

4. 复杂环境下样本生成与目标识别的方法及其应用, 国家自然科学基金联合基金重点项目，负责人, 252万，国家任务,202001--202312

5. 图像特征自动发现和提取及图像复原中的优化模型及算法研究, 国家自然科学基金面上项目，负责人, 50万，国家任务, 201601-201912

6. 大规模非负矩阵分解的优化模型和并行算法研究及应用, 国家自然科学基金青年基金项目，负责人,国家任务, 201201--201412

已指导学生

李聪杰  硕士研究生  070105-运筹学与控制论  

周柏村  硕士研究生  070105-运筹学与控制论  

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