Min Gan is a Full Professor with the College of Computer Science and Technology, Qingdao University, China. He received the B. S. degree in Computer Science and Engineering from Hubei University of Technology, Wuhan, China, in 2004, and the Ph.D. degree in Control Science and Engineering from Central South University, Changsha, China, in 2010. His research interests include image processing, machine learning, deep learning optimization, and computer vision. He currently serves as an Associate Editor for several flagship journals, including IEEE Transactions on Image Processing (TIP) and Pattern Recognition (Elsevier). He has also held significant leadership roles in the research community, notably serving as a Senior Program Chair for AAAI 2026. His work bridges theoretical foundations with practical methodologies in intelligent visual learning and computational intelligence.

E-mail: aganmin@aliyun.com

Publications

1. JiaJun Yu, Fang Yuan, Min GAN (甘敏, 通讯作者), Guang-Yong Chen. Active Arbitration: Decoupling Spatio-Temporal Duality for Efficient Traffic Forecasting, 35th International Joint Conference on Artificial Intelligence - 29th European Conference on Artificial Intelligence (IJCAI-ECAI 2026). In press.

    

2. Xiangxiang Su, Guang-Yong Chen, Min GAN (甘敏), C. L. Philip Chen. Towards Efficient Optimization of Sparse Regularized Separable Nonlinear Problems: A Novel Decoupled Strategy. Automatica. In press, 2026.

    

3. Guang-Yong Chen, Xiangxiang Su, Min GAN (甘敏, 通讯作者), Peng Xue, C. L. Philip Chen. An Efficient Algorithm for Nonlinear Regression Problems with Huber Loss. IEEE Transactions on Automatic Control. 2026, in press. DOI: 10.1109/TAC.2026.3683294

    

4. Deng-xiu Yu, Min GAN (甘敏, 通讯作者), Fang Yuan, Guang-Yong Chen. Accelerating Deep Network Learning: A Separable Block Coordinate Descent Approach with Recursive Least Squares, IEEE Transactions on Automatic Control. Major Revison.

5. Qibin Zhang, Licheng Liu, Min GAN (甘敏), C. L. Philip Chen. Rethinking the Role of Multi-scale Information in Window Attention for Single Image Super-Resolution, IEEE Transactions on Pattern Analysis and Machine Intelligence. Major Revison.

    

6. Min GAN (甘敏), Guang-Yong Chen, Yang Yi, Jing Chen, Lin Wang. A Saddle Point Remedy: Power of Variable Elimination. Submitted to IEEE Transactions on Pattern Analysis and Machine Intelligence.

    

7. Xiaowei Zhang, Xinglong Li, Mingliang Zhou, Min GAN (甘敏, 通讯作者), C. L. Philip Chen. ASCFormer: An Adaptive Strucure-aware Cascaded Transformer for 3D Object Detection. IEEE Transactions on Circuits and Systems for Video Technology, 2025, Digital Object Identifier: 10.1109/TCSVT.2025.3612592.

    

8. Min GAN (甘敏), Xiangxiang Su, Guang-Yong Chen, Jing Chen, C. L. Philip Chen. Online Learning Under A Separable Stochastic Approximation Framework. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2025, 47(2): 1317-1330.

    

9. Guodong Fan, Zishu yao, Guang-Yong Chen, Jian-Nan Su, Min GAN (甘敏, 通讯作者). IniRetinex: Rethinking Retinex-type Low-Light Image Enhancer via Initialization Perspective. The 39th Annual AAAI Conference on Artificial Intelligence. 2025.

    

10. Jian-nan Su, Guodong Fan, Min GAN (甘敏, 通讯作者), Guang-Yong Chen, C. L. Philip Chen. Revealing the Dark Side of Non-Local Attention in Single Image Super-Resolution. IEEE Transactions on Pattern Analysis and Machine Intelligence, September 2024, 46(12): 11476 - 11490.

     

11. Jian-nan Su, Min GAN (甘敏, 通讯作者), Guang-Yong Chen, Wenzhong Guo, C. L. Philip Chen. High-Similarity-Pass Attention for Single Image Super-Resolution. IEEE Transactions on Image Processing, 2024, 33: 610-624.

     

12. Jian-nan Su, Min GAN (甘敏, 通讯作者), Guang-Yong Chen, C. L. Philip Chen. Global Learnable Attention for Single Image Super-Resolution. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023, 45(7): 8453-8465.

13. Guang-Yong Chen, Peng Xue, Min GAN (甘敏, 通讯作者), Jing Chen, Wen-Zhong Guo, C. L. Philip Chen. Variable Projection Algorithms: Theoretical Insights and A Novel Approach for Problems with Large Residual. Automatica. Volume 177, July 2025, 112300.

     

14. Guodong Fan, Zishu yao, Guang-Yong Chen, Jian-Nan Su, Min GAN (甘敏, 通讯作者). IniRetinex: Rethinking Retinex-type Low-Light Image Enhancer via Initialization Perspective. The 39th Annual AAAI Conference on Artificial Intelligence. 2025.

     

15. Guang-Yong Chen, Min GAN (甘敏, 通讯作者), Long Chen, C. L. Philip Chen. Online identification of nonlinear systems with separable structure. IEEE Transactions on Neural Networks and Learning Systems, JUNE 2024, 35(6): 2162-2388.

16. Guang-Yong Chen, Hui-rang Xu, Min GAN. Riemannian Acceleration for Sparse PCA with Separable Structure and Second-Order Information Exploration. IEEE Transactions on Image Processing. In press.

17. Fang Yuan, Min GAN (甘敏, 通讯作者), Guang-Yong Chen. Efficient Splitting Approach for Symmetric Nonnegative Matrix Factorization. Submitted to Pattern Recognition.

18. Jin-fu Fan, Linqing Huang, Chaoyu Gong, Yang You, Min GAN (甘敏, 通讯作者), Zhongjie Wang. KMT-PLL: K-means Cross-attention Transformer for Partial Label Learning. IEEE Transactions on Neural Networks and Learning Systems, 2024, in press. 10.1109/TNNLS.2023.3347792

19. Xiang-xiang Su, Min GAN (甘敏, 通讯作者), Guang-Yong Chen, Lin Yang. Nonmonotone Variable Projection Algorithms for Matrix Decomposition with Missing Data, Pattern Recognition, 2024, Volume 148, 110150.

20. Guang-Yong Chen, Min GAN (甘敏, 通讯作者), Jing Chen, Long Chen. Embedded Point Iteration Based Recursive Algorithm for Online Identification of Nonlinear Regression Models. IEEE Transactions on Automatic Control. July, 2023, 68(7): 4257-4264.

21. Guo-dong Fan, Min GAN (甘敏, 通讯作者), C. L. Philip Chen. Multi-Scale Cross-connected Dehazing Network with Scene Depth Fusion. IEEE Transactions on Neural Networks and Learning Systems, 2024, 35(2): 1598-1612.

22. Guang-Yong Chen, Hui-lang Xu, Min GAN (甘敏, 通讯作者), C. L. Philip Chen. A Variable Projection-Based Algorithm for Fault Detection and Diagnosis. IEEE Transactions on Instrumentation & Measurement, 2023, 72:1-11.

     

23. Jing Chen, Min GAN (甘敏), Quanmin Zhu, Pritesh Narayan, Yanjun Liu. Robust standard gradient descent algorithm for ARX models using Aitken acceleration technique, IEEE Transactions on Cybernetics, 2022, 52(9): 9646-9655.

     

24. Guo-dong Fan, Bi Fan, Min GAN (甘敏, 通讯作者), C. L. Philip Chen. Multi-scale Low-light Image Enhancement Network with Illumination Constraint. IEEE Transactions on Circuits and Systems for Video Technology, 2022, 32(11): 7403-7417.

     

25. Guang-Yong Chen, Min GAN (甘敏, 通讯作者), Hong-Tao Zhu, C. L. Philip Chen. An Iterative Implementation of Variable Projection Algorithm for Separable Nonlinear Optimization Problems. IEEE Transactions on Systems, Man and Cybernetics: Systems, 2022, 52(11): 7259-7267.

26. Guang-Yong Chen, Min GAN (甘敏, 通讯作者), C. L. Philip Chen, Hong-Tao Zhu. Frequency Principle in Broad Learning System. IEEE Transactions on Neural Network and Learning Systems, 2022, 33(11): 6983-6989.

27. Jia Chen, Min GAN (甘敏, 通讯作者), Guang-Yong Chen, C. L. Philip Chen. Constrained Variable Projection Optimization for a Stationary RBF-AR Model. IEEE Transactions on Systems, Man and Cybernetics: Systems, 2022, 52(3): 1882-1890.

28. Min GAN (甘敏), Hong-Tao Zhu, Guang-Yong Chen, C. L. Philip Chen. Weighted Generalized Cross Validation Based Regularization for Broad Learning System. IEEE Transactions on Cybernetics, 2022, 52(5): 4064-4072.

29. Min GAN (甘敏), Yu Guan, Guang-Yong Chen, C. L. Philip Chen. Recursive Variable Projection Algorithm for a Class of Separable Nonlinear Models. IEEE Transactions on Neural Network and Learning Systems, 2021, 32(11): 4971-4982.

30. Guang-Yong Chen, Min GAN (甘敏, 通讯作者), C. L. Philip Chen, Han-Xiong Li. Basis Function Matrix based Flexible Coefficient Autoregressive Models: A Framework for Time Series and Nonlinear System Modeling. IEEE Transactions on Cybernetics, 2021, 51(2): 614-623.

31. Guang-Yong Chen, Min GAN (甘敏, 共同第一作者), Shu-qiang Wang, C. L. Philip Chen. Insights into Algorithms of Separable Nonlinear Least Squares Problems. IEEE Transactions on Image Processing, 2021, 30: 1207-1218.

32. Feng Zhou, Min GAN (甘敏, 通讯作者), C. L. Philip Chen. State-dependent ARX Model-based RPC with Variable Feedback Control Laws for Output Tracking, IEEE Transactions on Industrial Electronics, 2021, 68(5): 4228-4237.

     

33. Min GAN (甘敏), Guang-Yong Chen, Long Chen, C. L. Philip Chen. Term selection for a class of nonlinear separable models. IEEE Transactions on Neural Networks and Learning Systems, 2020, 31(2): 445 - 451.

34. Guang-Yong Chen, Shu-Qiang Wang, Dong-Qing Wang, Min GAN (甘敏, 通讯作者). Regularization Methods for Separable Nonlinear Models. Nonlinear Dynamics, 2019, 98: 1287–1298.

     

35. Min GAN (甘敏), Xiao-xian Chen, Ding Feng, Guang-Yong Chen, C. L. Philip Chen. Adaptive RBF-AR Models Based on Multi-innovation Least Squares Method. IEEE Signal Processing Letters, 2019, 26(8): 1182-1186.

36. Guang-Yong Chen, Min GAN (甘敏, 通讯作者), Feng Ding, C. L. Philip Chen. Modified Gram-Schmidt Method Based Variable Projection Algorithm for Separable Nonlinear Models. IEEE Transactions on Neural Networks and Learning Systems, 2019, 30(8): 2410-2418.

     

37. Guang-Yong Chen, Min GAN (甘敏, 通讯作者), C. L. Philip Chen, Han-Xiong Li. A Regularized Variable Projection Algorithm for Separable Nonlinear Least Squares Problems. IEEE Transactions on Automatic Control, 2019, 64(2): 526 – 537. (ESI高被引论文，hot topic论文)

     

38. Guang-Yong Chen, Min GAN (甘敏, 通讯作者), C. L. Philip Chen, Long Chen. A Two-Stage Estimation Algorithm Based on Variable Projection Method for GPS Positioning. IEEE Transactions on Instrumentation & Measurement, 2018, 67 (11): 2518 - 2525.

     

39. Min GAN (甘敏), C. L. Philip Chen, Guang-Yong Chen, Long Chen. On some separated algorithms for separable nonlinear squares problems [J]. IEEE Transactions on Cybernetics, 2018, 48(10): 2866-2874. (ESI高被引论文，hot topic论文)

     

40. Guang-Yong Chen, Min GAN (甘敏, 通讯作者). Generalized Exponential Autoregressive Models for Nonlinear Time Series: Stationarity, Estimation and Applications. Information Sciences, 2018，438：46-57.

     

41. Min GAN(甘敏), C. L. Philip Chen, Long Chen, Chun-yang Zhang. Exploiting the Interpretability and Forecasting Ability of the RBF-AR Model for Nonlinear Time Series [J]. International Journal of Systems Science, 2016, 47(8): 1868-1876.

     

42. Min GAN(甘敏), Han-Xiong Li, C. L. Philip Chen, Long Chen. A Potential Method for Determining Nonlinearity in Wind Data [J], IEEE Power and Energy Technology Systems Journal, 2015, 2(2): 74-81.

     

43. Min GAN(甘敏), C. L. Philip Chen, Han-Xiong Li, Long Chen. Gradient radial basis function based varying-coefficient Autoregressive Model for nonlinear and nonstationary time series [J]. IEEE Signal Processing Letters, 2015, 22(7): 809-812.

     

44. Min GAN(甘敏), Han-Xiong Li, Hui Peng. A variable projection approach for efficient Estimation of RBF-ARX model [J]. IEEE Transactions on Cybernetics, 2015, 45(3): 476-485.

     

45. Chun-yang Zhang, C. L. Philip Chen, Long Chen, Min Gan(甘敏). Fuzzy Restricted Boltzmann Machine to Enhance Deep Learning [J]. IEEE Transactions on Fuzzy Systems, 2015, 23(6): 2163-2173.

     

46. Min GAN(甘敏), Han-xiong LI. An Efficient Variable Projection Formulation for Separable Nonlinear Least Squares Problems [J]. IEEE Transactions on Cybernetics, 2014, 44(5): 707-711.

     

47. Chun-yang Zhang, C. L. Philip Chen, Min Gan(甘敏). Predictive Deep Boltzmann Machine for Multi-Period Wind Speed forecasting [J]. IEEE Transactions on sustainable energy, 2015, 6(4): 1416-1425.

     

48. Min Gan(甘敏), Yu Cheng, Kai Liu, Gang-lin Zhang. Seasonal time series prediction based on a quasi-linear autoregressive model [J]. Applied Soft Computing, 2014, 24(1): 13-18.

     

49. Min GAN(甘敏), Yun-zhi Huang, Ming Ding, Xue-ping Dong. Testing for nonlinearity in solar radiation time series by a fast method of surrogate data [J]. Solar Energy, 2012, 86(9): 2893-2896.

     

50. Min Gan(甘敏), Hui Peng, Liyuan Chen. A Global-local Approach to Parameter Optimization of RBF-type Models [J]. Information Sciences, 2012, 197(15): 144-160.

     

51. Min Gan(甘敏), Hui Peng, Xueping Dong. A hybrid algorithm to optimize RBF network architecture and parameters for nonlinear time series modeling [J]. Applied Mathematical Modelling, 2012, 36(7): 2911-2919.

     

52. Min Gan(甘敏), Hui Peng. Stability analysis of RBF-network based state-dependent autoregressive model for nonlinear time series [J]. Applied Soft Computing, 2012, 12(1): 174-181.

     

53. Min Gan(甘敏), Ming Ding, Yun-zhi Huang, Xueping Dong. The effect of different state sizes on Mycielski approach for wind speed prediction [J]. Journal of Wind Engineering & Industrial Aerodynamics, 2012, 109:89-93.  

     

54. Min Gan(甘敏), Hui Peng, et al. A locally linear RBF network-based state-dependent AR model for nonlinear time series modeling [J]. Information Sciences, 2010, 180: 4370~4383.

     

55. Min Gan(甘敏), Hui Peng, et al. An Adaptive Decision Maker for Constrained Evolutionary Optimization [J]. Applied Mathematics and Computation, 2010, 215(12): 4172~4184.

     

56. 甘敏，丁明，董学平. 基于改进的Mycielski方法的风速时间序列预测[J]. 系统工程理论与实践，2013, 33(4) : 1084-1088.

57. 甘敏，彭辉，黄云志，董学平. 自组织状态空间模型参数初始分布搜索算法[J].自动化学报，2012, 38(9): 1538-1543.

58. 甘敏，彭辉，陈晓红. 基于金融市场微结构模型和进化算法的动态资产分配[J].系统工程学报. 2011，26(3): 314-321.

59. 甘敏，彭辉，陈晓红. RBF-AR模型在非线性时间序列预测中的应用[J].系统工程理论与实践. 2010，30(6)：1055~1061.

60. 甘敏，彭辉，王勇. 多目标优化与适应惩罚的混合约束优化进化算法[J]. 控制与决策, 2010, 25(3): 378~382.

61. 甘敏，彭辉.不同基函数对RBF-ARX 模型的影响研究[J].中南大学学报. 2010, 41(6): 2231~2235.

62. 甘敏，彭辉. 基于带回归权重的RBF-AR模型的混沌时间序列预测[J]. 系统工程与电子技术， 2010，32(4)：820~824.

63. 甘敏，彭辉. RBF神经网络参数优化的两种混合优化算法[J]. 控制与决策, 2009, 24(8): 1172~1176.