Scholar
Nannan Wu (吴南楠)
Google Scholar ID: yCV07qQAAAAJ
Hong Kong Polytechnic University & Huazhong University of Science and Technology
Citations & Impact
Citations
153
H-index
5
i10-index
4
Publications
10
Co-authors
6
list available
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- Multiple papers accepted by top conferences such as MICCAI 2024, AAAI 2024, IJCAI 2024. Specific papers include:
- - FedMLP: Federated Multi-Label Medical Image Classification
- - FedIA: Federated Medical Image Segmentation
- - From Optimization to Generalization: Fair Federated Learning
- - FedA3I: Annotation Quality-Aware Aggregation for Federated Medical Image Segmentation
- - DTMFormer: Dynamic Token Merging for Boosting Transformer-based Medical Image Segmentation
- - FedIIC: Robust Federated Learning for Class-Imbalanced Medical Image Classification
- - FedNoRo: Noise-Robust Federated Learning by Addressing Class Imbalance and Label Noise Heterogeneity
Research Experience
- Invited to give talks at various conferences and workshops, including CSIG, AI Time, etc. Attended IJCAI-23 and gave oral and poster presentations. Served as a reviewer for PRCV 2023.
Education
- Dual Ph.D. Student: Department of Computing, The Hong Kong Polytechnic University (Advisors: Prof. Changwen Chen, Prof. Li Yu); School of Electronic Information and Communications, Huazhong University of Science and Technology (Advisor: Prof. Zengqiang Yan). B.Eng. Degree: Graduated from HUST in 2022.
Background
- Research Interests: Trustworthy machine learning, with a current emphasis on federated learning. Brief Bio: Currently a dual Ph.D. student at the Department of Computing, The Hong Kong Polytechnic University (PolyU) and the School of Electronic Information and Communications, Huazhong University of Science and Technology (HUST).
Miscellany
- Personal interests and hobbies not mentioned
