潘炎

副教授

联系邮箱： panyan5@mail.sysu.edu.cn

教师简介: 

潘炎，副教授，博士生导师。2007年在中山大学计算机科学系计算机软件与理论专业获得工学博士学位（导师：汤庸教授）。2012年在新加坡国立大学的Learning and Vision Research Group做访问研究员（合作导师：颜水城教授）。在IEEE TIP，IEEE TNNLS，IEEE TCB，IEEE TC等国际期刊和CVPR/AAAI/SIGIR/ECCV等国际会议上发表论文50多篇。主持国家自然基金面上项目3项，国家基金青年基金项目1项。

研究领域: 

主要研究兴趣是多模态大模型、信息检索与推荐、因果推断，包括

1、多模态大模型幻觉抑制、多模态问答、因果推断在大模型中的应用

2、基于深度神经网络的哈希方法，图像检索

3、生成式推荐，排序融合、排序学习

主持的科研项目: 

国家自然基金面上项目，因果驱动的多模态大模型幻觉抑制的关键技术研究，2027-2030

国家自然基金面上项目，基于深度神经网络的相似性保持哈希的关键技术研究，2018-2021

国家自然基金面上项目，基于低秩矩阵学习的多源排序融合关键技术研究，2014-2017

国家自然基金青年基金项目（C类），半监督排序学习理论与算法研究，2011-2013

教授课程: 

人工神经网络

数据结构与算法

学术论文: 

  1. Qinkang Gong, Yan Pan*, Hanjiang Lai, Rongbang Qiu, Jian Yin:Causal-TSF: A Causal Intervention Approach to Mitigate Confounding Bias in Time Series Forecasting. IEEE Transactions on Knowledge and Data Engineering. 37(6): 3205-3219 (2025).
  2. Qinkang Gong，Yan Pan*, Hanjiang Lai, Jian Yin.A Causal Intervention Method for Domain Generalization with a Self-Supervised AuxiliaryTask. International Jouranl on Computer Vision, 133(10): 7110-7127 (2025).
  3. Liangdao Wang, Yan Pan*, Cong Liu, Hanjiang Lai, Jian Yin, Ye Liu.Deep Hashing with Minimal-Distance-Separated Hash Centers.IEEE international conference on computer vision and pattern recognition (CVPR): 23455-23464
  4. Yuchen Liang, Yan Pan*, Hanjiang Lai, Wei Liu, Jian Yin. Deep Listwise Triplet Hashing for Fine-grained Image Retrieval.IEEE Transactions on Image Processing, 2022, 31(1): 949-961.
  5. Jielong Chen, Yan Pan*,Yunong Zhang. Model-Free and Pseudoinverse-Free Zhang Neurodynamics Scheme for Robotic Arms’ Path Tracking Control. IEEE Transactions on Neural Networks and Learning Systems. 36(6): 10201-10212 (2025) 
  6. Yan Pan, Chang-Qin Huang, Dianhui, Wang. Multiview Spectral Clustering via Robust Subspace Segmentation.IEEE Transactions on Cybernetics,2022, 52(4): 2467-2476.
  7. Geyang Ke，Yan Pan*, Jian Yin, Changqin Huang. Optimizing Evaluation Metrics for Multi-Task Learning via the Alternating Direction Method of Multipliers.IEEE Transactions on Cybernetics,48(3):993-1006,2018.
  8. Chang-Qin Huang, Shang-Ming Yang,Yan Pan*, Han-Jiang Lai. Object-Location-Aware Hashing for Multi-Label Image Retrieval via Automatic Mask Learning.IEEE Transactions on Image Processing, 2018, 27(9)：4490-4502.
  9. Hanjiang Lai, Yan Pan* Xiangbo Xiao, Yunchao Wei, Shuicheng Yan. Instance-Aware Hashing for Multi-Label Image Retrieval, IEEE Transactions on Image Processing, 22(6):2469-2479, 2016
  10. Yan Pan, Rongkai Xia, Jian Yin, and Ning Liu. A Divide-and-Conquer Method for Scalable Robust Multi-Task Learning. IEEE Transaction on Neural Networks and Learning Systems, 26(12): 3163-3175, 2015. 
  11. Hanjiang Lai, Yan Pan*, Shuicheng Yan. Simultaneous Feature Learning and Hash Coding with Deep Neural Networks. In Proceedings of IEEE International Conference on Computer Visionand Pattern Recognition(CVPR), 2015.
  12. Rongkai Xia, Yan Pan*, Hanjiang Lai, Cong Liu, and Shuicheng Yan. Supervised Hashing for Image Retrieval via Image Representation Learning. In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), 2014.
  13. Rongkai Xia, Yan Pan*, Lei Du, and Jian Yin. Robust Multi-View Clustering via Low-rank and Sparse Decomposition. In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), 2014.
  14. Yan Pan, Hanjiang Lai, Cong Liu, Yong Tang, and Shuicheng Yan. Rank Aggregation via Low-rank and Structured-sparse Decomposition. In proceedings of AAAI conference on artificial intelligence (AAAI), 2013.
  15. Yan Pan, Hanjiang Lai, Cong Liu, and Shuicheng Yan. A Divide-and-Conquer Method for Scalable Low-rank Latent Matrix Pursuit. In proceedings of IEEE international conference on computer vision and pattern recognition (CVPR), 2013.