Short Bio
I am an Associate Researcher (2024-) in the School of Artificial Intelligence at Nanjing University. I am a member of LAMDA Group.
Previously, I received my Ph.D. (2018-2024) from Nanjing University, advised by Prof. De-Chuan Zhan and Prof. Han-Jia Ye.
I was fortunate to visit MMLab@NTU (2022-2023), working closely with Prof. Ziwei Liu.
My research interests include machine learning and its applications in computer vision, currently focusing on continual learning, pre-trained model reuse, and multimodal large language models.
I am seeking highly self-motivated students. If interested, please email me your resume and transcript.
News
Selected Publications

For more details, please view the full publication page or Google Scholar profile.
Conference Paper
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ICCV
External Knowledge Injection for CLIP-Based Class-Incremental Learning
Da-Wei Zhou, Kai-Wen Li, Jingyi Ning, Han-Jia Ye, Lijun Zhang, De-Chuan Zhan
International Conference on Computer Vision. ICCV 2025
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Paper]
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Code]
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ICCV
Integrating Task-Specific and Universal Adapters for Pre-Trained Model-Based Class-Incremental Learning
Yan Wang, Da-Wei Zhou, Han-Jia Ye
International Conference on Computer Vision. ICCV 2025
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Paper]
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Code]
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CVPR
Dual Consolidation for Pre-Trained Model-Based Domain-Incremental Learning
Da-Wei Zhou, Zi-Wen Cai, Han-Jia Ye, Lijun Zhang, De-Chuan Zhan
The IEEE/CVF Conference on Computer Vision and Pattern Recognition. CVPR 2025
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Paper]
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Code]
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Media]
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CVPR
Task-Agnostic Guided Feature Expansion for Class-Incremental Learning
Bowen Zheng, Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan
The IEEE/CVF Conference on Computer Vision and Pattern Recognition. CVPR 2025
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Paper]
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Code]
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ICML
Addressing Imbalanced Domain-Incremental Learning through Dual-Balance Collaborative Experts
Lan Li, Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan
International Conference on Machine Learning. ICML 2025
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Paper]
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Code]
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IJCAI
A Unifying Perspective on Model Reuse: From Small to Large Pre-Trained Models
Da-Wei Zhou, Han-Jia Ye
International Joint Conference on Artificial Intelligence. IJCAI 2025
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Paper]
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Project Page]
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CVPR
Expandable Subspace Ensemble for Pre-Trained Model-Based Class-Incremental Learning
Da-Wei Zhou, Hai-Long Sun, Han-Jia Ye, De-Chuan Zhan
The IEEE/CVF Conference on Computer Vision and Pattern Recognition. CVPR 2024
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Paper]
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Code]
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IJCAI
Continual Learning with Pre-Trained Models: A Survey
Da-Wei Zhou, Hai-Long Sun, Jingyi Ning, Han-Jia Ye, De-Chuan Zhan
International Joint Conference on Artificial Intelligence. IJCAI 2024
Top-4 Most Influential IJCAI Papers
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Paper]
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Code]
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Media]
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ICML
Multi-layer Rehearsal Feature Augmentation for Class-Incremental Learning
Bowen Zheng, Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan
International Conference on Machine Learning. ICML 2024
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Paper]
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Code]
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ICLR Spotlight
A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental Learning
Da-Wei Zhou, Qi-Wei Wang, Han-Jia Ye, De-Chuan Zhan
International Conference on Learning Representations. ICLR 2023 Spotlight Presentation
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Paper]
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Code]
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ICLR
BEEF: Bi-Compatible Class-Incremental Learning via Energy-Based Expansion and Fusion
Fu-Yun Wang, Da-Wei Zhou, Liu Liu, Yatao Bian, Han-Jia Ye, De-Chuan Zhan, Peilin Zhao
International Conference on Learning Representations. ICLR 2023
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Paper]
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Code]
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NeurIPS
Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration
Qi-Wei Wang, Da-Wei Zhou, Yi-Kai Zhang, De-Chuan Zhan, Han-Jia Ye
Neural Information Processing Systems. NeurIPS 2023
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Paper]
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Code]
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CVPR
Forward Compatible Few-Shot Class-Incremental Learning
Da-Wei Zhou, Fu-Yun Wang, Han-Jia Ye, Liang Ma, Shiliang Pu, De-Chuan Zhan
IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2022
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Paper]
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Code]
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Project Page]
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ECCV
FOSTER: Feature Boosting and Compression for Class-Incremental Learning
Fu-Yun Wang, Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan
European Conference on Computer Vision. ECCV 2022
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Paper]
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Code]
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CVPR Oral
Learning Placeholders for Open-Set Recognition
Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan
IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2021
Oral Presentation
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Paper]
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Code]
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Project Page]
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ACM MM
Co-Transport for Class-Incremental Learning
Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan
ACM International Conference on Multimedia. ACM MM 2021
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Paper]
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Code]
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Project Page]
Journal Article
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TPAMI
Learning without Forgetting for Vision-Language Models
Da-Wei Zhou, Yuanhan Zhang, Yan Wang, Jingyi Ning, Han-Jia Ye, De-Chuan Zhan, Ziwei Liu
IEEE Transactions on Pattern Analysis and Machine Intelligence. TPAMI 2025
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Paper]
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Code]
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Media]
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TPAMI
Class-Incremental Learning: A Survey
Da-Wei Zhou, Qi-Wei Wang, Zhi-Hong Qi, Han-Jia Ye, De-Chuan Zhan, Ziwei Liu
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Code]
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TPAMI
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IJCV
Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You Need
Da-Wei Zhou, Zi-Wen Cai, Han-Jia Ye, De-Chuan Zhan, Ziwei Liu
International Journal of Computer Vision. IJCV 2025
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Paper]
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Code]
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Media]
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TPAMI
Contextualizing Meta-Learning via Learning to Decompose
Han-Jia Ye, Da-Wei Zhou, Lanqing Hong, Zhenguo Li, Xiu-Shen Wei, De-Chuan Zhan
IEEE Transactions on Pattern Analysis and Machine Intelligence. TPAMI 2024
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Paper]
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Code]
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SCIS
PyCIL: A Python Toolbox for Class-Incremental Learning
Da-Wei Zhou*, Fu-Yun Wang*, Han-Jia Ye, De-Chuan Zhan
SCIENCE CHINA Information Sciences. SCIS 2023
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Code]
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Media]
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中文解读]
- Office: A202, Yifu Building
- Email: zhoudw (at) lamda.nju.edu.cn or zhoudw (at) nju.edu.cn
Many thanks to Yaoyao for sharing this great theme.