彭亚新 Peng Yaxin

职务/职称：Professor

邮箱：yaxin.peng@shu.edu.cn

电话：13636337103

研究领域：Geometric variational method, Manifold learning, Metric learning, Structure preserving based Statistic learning, Data mining and processing, Reinforcement Learning

教育经历：

2005.9-2008.9 Ecole Normale Superieur de Lyon, UMLP PHD of ENS-Lyon, PHD (O.Druet)

East China Normal University, Department of Mathematics, PHD (沈纯理)

2002.9-2005.7 East China Normal University, Department of Mathematics, Master (郑宇)

1998.9-2002.7 Anhui Normal University, Department of Mathematics, Bachelor

工作经历：

2008.9-至今 Shanghai University, Department of Mathematics

2012.2-2013.2 Visiting Scholars to Arizona state University（Jieping Ye）

代表性科研项目：

NSFC: 12026416, Thematic Workshop on the theories of Geometry and PDE with their applications on Data Analysis

NSFC: 11771276, Geometric Model and Intrinsic algorithm for atlas of 3D medical images

NSFC: 11101260, Geometric flow and its applications to medical image processing

NSFC: 11026149, Beltrami flow and its applications to medical image processing

代表性学术论文：

- W. Wang, Y. Zhu, Y. Zhou, C. Shen, J. Tang, Z. Xu, Y. Peng*, Y. Zhang*, Exploring Gradient Explosion in Generative Adversarial Imitation Learning: A Probabilistic Perspective, Accepted, AAAI 2024 (CCF A区)

-J. Yang, J.Zhu, X. Ding, Y. Peng*, Y. Zhang*, A memory pool variational autoencoder framework for cross-domain recommendation, Expert Systems with Applications, Volume 241, 2024, 122771 (中科院一区, IF= 8.5)

-Z..Ma, J. Hou, W. Zhu, Y. Peng*, Y. Li*, PMNN: Physical model-driven neural network for solving time-fractional differential equations, Chaos, Solitons & Fractals, Volume 177, 2023,114238 (中科院一区, IF= 7.8)

-Y. Chen, Z. Jia, Y. Peng* and Y. Peng*, "Efficient Robust Watermarking Based on Structure-Preserving Quaternion Singular Value Decomposition," in IEEE Transactions on Image Processing, vol. 32, pp. 3964-3979, 2023, doi: 10.1109/TIP.2023.3293773. (中科院一区, IF= 10.6)

- Y. Zhou, M. Lu, X. Liu, Z. Che, Z. Xu, J. Tang, Y. Zhang, Y. Peng and Y. Peng*, Distributional Generative Adversarial Imitation Learning with Reproducing Kernel Generalization, Neural Networks, accepted, 16 May 2023. (中科院一区, IF= 9.657)

-Y. Huang, N. Liu, Z. Che, Z. Xu, C. Shen, Y. Peng, G. Zhang*, X. Liu, F. Feng, J. Tang, “CP3: Channel pruning plug-in for point cloud network,” in CVPR, pp. 5302-5312 ,28 Feb 2023. (CCF A区)

- X. Ding; C. Shen; T. Zeng; Y. Peng*; SAB Net: A semantic attention boosting framework for semantic segmentation, IEEE Transactions on Neural Networks and Learning Systems, 2022, doi: 10.1109/TNNLS.2022.3144003. (中科院一区，IF=14.225)

-Y. Zhou, Y. Zhang, X. Liu, W. Wang, Z. Che, Z. Xu, J. Tang, and Y. Peng*，Generalization and Computation for Policy Classes of Generative Adversarial Imitation Learning，PPSN 2022, LNCS 13398, pp. 385–399, 2022.

- X. Ding; T. Zeng; J. Che；Z. Che; Y. Peng*; SRRNet: A Semantic Representation Refinement Network for Image Segmentation, IEEE Transactions on Multimedia, 2022. (中科院一区，IF=8.182/Q1)

-Y. Huang, X. Liu, Y. Zhu, Z. Xu, C. Shen, Z. Che, G. Zhang, Y. Peng, F. Feng, J. Tang, “Label-guided auxiliary training improves 3D object detector,” in ECCV, 684-700, 2022.

- X. Ding; C. Shen; Z. Che; T. Zeng; Y. Peng*; SCARF: A semantic constrained attention refinement network for semantic segmentation, in IEEE International Conference on Computer Vision Workshops (ICCVW-21 Best student award), 2021: 3002-3011.

-X. Ding，Y Peng*，C. Shen，T. Zeng CAB U-Net: An end-to-end category attention boosting algorithm for segmentation, Computerized Medical Imaging and Graphics, 84,101764, 2020.

- S.Ying, L. Cai, C. He, Y. Peng*, Geometric understanding for unsupervised subspace learning. in International Joint Conference on Artificial Intelligence (IJCAI). 4171-4177, 2019. (CCF A区)

-Z. Wen, M. Sun, Y. Li, S.Ying, Y. Peng*. Asymmetric Local Metric Learning with PSD Constraint for Person Re-identification. International Conference on Robotics and Automation (ICRA) :4862-4868, 2019

-S.Ying, X. Zhang, Y. Peng*, D. Shen. Longitudinal Image Analysis via Path Regression on the Image Manifold. Journal of the Operations Research Society of China. 7(4):599-614, 2019.

- Y. Peng. L. Hu, S.Ying, C.Shen*. Global nonlinear metric learning by gluing local linear metrics. in SIAM International Conference on Data Mining, 423-431, 2018.

- S.Ying, Z. Wen, J, Shi, Y. Peng*, J. Peng, H. Qiao, Manifold preserving: an intrinsic approach for semi-supervised distance metric learning, IEEE Transactions on Neural Networks and Learning Systems. 29(7):2731-2742, 2018. (中科院一区，IF=14.225)

- Y. Peng, Bao LL, Pi L*, Object(s)-of-interest segmentation for images with inhomogeneous intensities based on curve evolution. Neurocomputing. 195:13-18, 2016.

（最后更新日期：2023.12.9）