Shangde Gao (高尚德)

gaosde@zju.edu.cn

Hangzhou, Zhejiang, China

I am currently a Postdoctoral Researcher at the School of Medicine, Zhejiang University. I received my Ph.D. from the College of Computer Science and Technology, Zhejiang University, in December 2025, under the supervision of Prof. Jian Wu. During my doctoral studies, I was affiliated with ZJU RealLab, Liangzhu Lab, and the Center for Data Science.

I received my M.S. in Computer Science from Hunan University in 2020, advised by Prof. Xin Liao, and my B.S. in Software Engineering from Hunan University in 2017.

My research focuses on computer vision and AI for science, with particular interest in knowledge distillation, knowledge fusion, and robust methods for real-world image classification and segmentation.

You can find my work on Google Scholar or GitHub.

Latest news 🔥🔥🔥

Aug 28, 2026	One paper was accepted by BMVC 2026, congratulations to Hexiang.
Jul 09, 2026	One paper was accepted by Expert Systems with Applications.
Jun 08, 2026	One paper was accepted by CVPR 2026 and selected as oral presentation and Award Candidate!
Mar 26, 2026	One paper was accepted by IEEE Transactions on Computational Social Systems 2026.
Mar 04, 2026	One paper was accepted by Neural Networks 2026.

Selected publications

Bridging Global Context and Directional Anisotropy: A Synergistic Mamba-AFF Framework for 3D Brain Tumor Segmentation

Qi Wang, Hongxia Xu, Shangde Gao, and 3 more authors

Expert Systems with Applications, 2026

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R2-Seg: Training-Free OOD Medical Tumor Segmentation via Anatomical Reasoning and Statistical Rejection

Shuaike Shen, Ke Liu, Jiaqing Xie, and 5 more authors

In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2026

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Towards generalizable retina vessel segmentation with deformable graph priors

Ke Liu, Shangde Gao, Yichao Fu, and 1 more author

Advances in Neural Information Processing Systems, 2026

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Few-Shot Medical Image Segmentation With Hierarchical Hypercorrelation Vision State-Space Model

Zheng Cao, Bang Du, Danqing Hu, and 4 more authors

IEEE Transactions on Computational Social Systems, 2026

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LLM-SDaT: A knowledge-informed LLM framework for syndrome differentiation in TCM

Bingtao Guan, Shangde Gao, Dawei Zheng, and 4 more authors

Neural Networks, 2026

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Uncertainty-aware multi-expert knowledge distillation for imbalanced disease grading

Shuo Tong, Shangde Gao, Ke Liu, and 4 more authors

In International Conference on Medical Image Computing and Computer-Assisted Intervention, 2025

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Probabilistic Integration of Renal Cancer Radiology and Pathology Using Graph Neural Networks

Shangqi Gao, Shangde Gao, Ines Machado, and 1 more author

In International Conference on Medical Image Computing and Computer-Assisted Intervention, 2025

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KA^2ER: Knowledge Adaptive Amalgamation of ExpeRts for Medical Images Segmentation

Shangde Gao, Yichao Fu, Ke Liu, and 2 more authors

In Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024

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Collaborative Knowledge Amalgamation: Preserving Discriminability and Transferability in Unsupervised Learning

Shangde Gao, Yichao Fu, Ke Liu, and 4 more authors

Information Sciences, 2024

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Contrastive Knowledge Amalgamation for Unsupervised Image Classification

Shangde Gao, Yichao Fu, Ke Liu, and 1 more author

In International Conference on Artificial Neural Networks (ICANN), 2023

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PCVAE: A Physics-Informed Neural Network for Determining the Symmetry and Geometry of Crystals

Ke Liu, Shangde Gao, Kaifan Yang, and 1 more author

In International Joint Conference on Neural Networks (IJCNN), 2023

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