一、基本情况

汪梦竹，博士，河北工业大学准聘副教授，元光学者，硕士生导师。分别于2018年和2023年在重庆大学获得硕士学位和国防科技大学获得博士学位。研究方向为机器学习及迁移学习。目前在机器学习与人工智能领域顶级期刊（IEEE TIP, IEEE TKDE, IEEE TNNLS）和顶级会议（CVPR, AAAI, ACMMM, ICML, ICLR）发表论文70余篇。担任人工智能顶级会议ICML, ICLR, AAAI，NeurIPS的程序委员会成员。

二、硕导所属（含跨转）学科、专业学位类别

1、计算机学科（或专业学位类别）

研究方向一：迁移学习

研究方向二：无监督域适应

研究方向三：域泛化

2、生物信息交叉（或专业学位类别）

研究方向一：单细胞多组学

研究方向二：医学图像分割

研究方向三：大模型对齐

三、主持、参与的科研及教研项目情况（含获奖情况）

国家自然科学青年基金，基于数据增强的迁移学习方法与理论研究，主持，2025.01-2027.12

天津市自然科学青年基金，面向数据驱动的可见与不可见的迁移学习方法研究，主持，2025.01-2026.10

四、近年来发表代表性论文情况（仅限第一作者或通讯作者），主编或参编的教材、专著情况，获得专利情况等

1. Mengzhu Wang, H Su, et al.(2025) Graph Convolutional Mixture-of-Experts Learner Network for Long-Tailed Domain Generalization, TCSVT （中国科学院一区）

2. Mengzhu Wang. (2025) SimProF: A Simple Probabilistic Framework for Unsupervised Domain Adaptation，AAAI （中国科学院一区）

3. Mengzhu Wang, J Chen, H Wang, H Wu, Z Liu,Q Zhang. (2023). Interpolation Normalization for Contrast Domain Generalization. ACMMM (CCF-A 会议)

4. Mengzhu Wang, J Yuan, Z Wang.(2023).Mixture-of-Experts Learner for Single Long-Tailed Domain Generalization. (ACMMM) (CCF-A 会议oral)

5. Mengzhu Wang, J Yuan, Q Qian, Z Wang, H Li.(2022).Semantic Data Augmentation based Distance Metric Learning for Domain Generalization. (ACMMM) (CCF-A 会议oral).

6. Mengzhu Wang, W Wang, BLi, X Zhang, L Lan, H Tan, T Liang, W Yu, Z Luo.(2021).Interbn:Channel fusion for adversarial unsupervised domain adaptation, (ACMMM) (CCF-A 会议oral).

7. Mengzhu Wang, X Zhang, L Lan,Z Luo.Equity in Unsupervised Domain Adaptation by Nuclear Norm Maximiza- tion, IEEE Transactions on Circuits and Systems for Video Technology (TCSVT) (中国科学院一区)

8. MengzhuWang, X Zhang,L Lan,Z Luo. Smooth-GuidedImplicit Data Augmentation for Domain Generalization, IEEE Transactions on Neural Networks and Learning Systems (TNNLS) (中国科学院一区)

9. Mengzhu Wang, X Zhang,L Lan, Z Luo. Inter-Class and Inter-Domain Semantic Augmentation for Domain Gener- alization, IEEE Transactions on Image Processing (TIP) (CCF-A)

10. Mengzhu Wang, J Chen, Y Wang, Z Gong, K Wu, C.M.Leung.(2023) TFC: Transformer Fused Convolution for Adversarial Domain Adaptation, IEEE Transactions on Computational Social Systems (中国科学院二区, if = 5)

11. N Yin*, Mengzhu Wang*, B Gu, X Luo, DREAM: Dual Structured Exploration with Mixup for Open-set Graph Domain Adaption, 2024, International Conference on Learning Representations (ICLR) (共同一作)

12. H Su,W Luo,D Liu,Mengzhu Wang*, J Tang,J Chen,CWang,Z Chen.(2024).Sharpness-AwareModel-Agnostic Long-Tailed Domain Generalization, AAAI(CCF- A 会议, 通讯作者).

13. T Liang, B Li, Mengzhu Wang*, H Tan, Z Luo.A Closer Look at the Joint Training of Object Detection and Re- identificationinMulti-ObjectTracking,IEEETransactionsonImageProcessing(CCF-A期刊, 通讯作者)

14. Mengzhu Wang, J Chen, Y Wang, Z Chen, (2023) Joint Adversarial Domain Adaptation With Structural Graph Alignment, IEEE Transactions on Network Science and Engineering (中国科学院二区

15. Mengzhu Wang, S Wang, W Wang, T Liang, J Chen, Z Luo.(2023) Reducing Bi-level Feature Redundancy for Unsupervised Domain Adaptation. Pattern Recognition (中国科学院一区)

16. W Wang, Mengzhu Wang*, Z Wang, H Li, Z Wang.(2023) Importance filtered soft label-based deep adaptation network. Knowledge-Based Systems (中国科学院一区, 通讯作者)

17. W. Wang, Mengzhu Wang*, X Dong,L Lan,Q Zu,X Zhang, C Wang.(2023).Class-specific and Self-learning Local Manifold Structure for Domain Adaptation. Pattern Recognition (中国科学院一区)

18. Mengzhu Wang, P Li, L Shen, Y Wang, S Wang, W Wang, X Zhang, J Chen, Z Luo.(2022).Informative Pairs Mining based Adaptive Metric Learning for Adversarial Domain Adaptation, Neural Networks(中国科学院一区, if=7.8).

19. Mengzhu Wang, S Wang,Y Wang,T Liang,J Chen,Z Luo.(2023) Boosting Unsupervised Domain Adaptation:A Fourier approach, Knowledge-Based Systems (中国科学院一区)

20. MengzhuWang, S An,X Luo,X Peng,W Yu,J Chen,Z Luo.(2022).Attention-based Adversarial Partial Domain Adaptation,IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (CCF-B).

五、联系人：汪梦竹，  联系方式：dreamkily@gmail.com