About Me

Guangze Shi is currently a Ph.D. candidate in the College of Computer Science and Technology at Taiyuan University of Technology. His advisor is Professor Mingqiang Wei. He has published four papers in SCI journals and renowned conferences, including CVPR, MICCAI, MedIA and IEEE J-BHI.

Guangze Shi’s research focuses on computer vision and medical data analytics. His interests include foundation models, domain generalization in computer vision, as well as pathological image analysis and multimodal data analysis in medical data analytics.

📜 Research Area

• Computer Vision:

Foundation model, Domain generalization

• Medical Data Analytics:

Pathological image analysis, Multimodal data analysis

💻 Research Experiences

• 2018.09 - 2022.07: B.ENG. in Software Engineering, Taiyuan University of Technology, China
• 2023.09 - 2025.07: M.ENG. in Big Data Technology and Engineering, Taiyuan University of Technology, China
• 2025.09 - Present: Ph.D candidate in Computer Science and Technology, Taiyuan University of Technology, China

📝 Publications

2026

• [1] Guangze Shi, Yingjie Mi, Jia Shen, Feixue Shao, Jiarui Cao, Yexin Lai, Xueyu Liu*, Rui Wang, Yongfei Wu, Mingqiang Wei*. PromptPilot: Game-Theoretic Multi-Agent Prompt Optimization for Segment Anything, International Conference on Machine Learning (ICML), 2026. (CCF A)
• [2] Xueyu Liu, Xiaoyi Zhang, Meilin Liu, Guangze Shi, Jia Shen, Yujie Wang, Cai Zhao, Ziyuan He, Yongfei Wu*, Mingqiang Wei, Yongle Chen*. Attack for Defense: Adversarial Agents for Point Prompt Optimization Empowering Segment Anything Model, Conference on Computer Vision and Pattern Recognition (CVPR), 2026. (CCF A)
• [3] Shuqi Xia, Guangze Shi, Jiarui Cao, Aoyuan Shi, Meilin Liu, Xiaoyi Zhang, Yujie Wang, Xueyu Liu*, Cai Zhao, Ziyuan He, Yongfei Wu, Mingqiang Wei. Instruction-Focus-Prompt：Semantics-Driven Structural Prompts for Universal SAM Segmentation, Conference on Computer Vision and Pattern Recognition Findings (CVPR Findings), 2026.
• [4] Helin Wang, Guangze Shi, Xueyu Liu*, Jianan Zhang, Sheng Chen, Jiashuo Shi, Yu-ang Li, Guanghui Yue, Yongfei Wu*. Explainable AI in Medicine: A Comprehensive Narrative Review of Methods, Applications, and Future Directions, Expert Systems, 2026. (Review)

2025:

• [1] Guangze Shi, Ying Wang, Yongfei Wu*, Xueyu Liu*, Jia Shen, Hao Meng, Yexin Lai, Weixia Han, Yan Hu, Mingqiang Wei. Al-driven Quantitative Analysis of Pathological images for Membranous Nephropathy across Macro and Micro Modalities, IEEE Journal of Biomedical and Health Informatics (IEEE J-BHI), 2025. (SCI Q2-TOP)
• [2] Xueyu Liu, Guangze Shi, Rui Wang, Yexin Lai, Jianan Zhang, Weixia Han, Min Lei, Ming Li, Xiaoshuang Zhou, Yongfei Wu*, Chen Wang, Wen Zheng. Segment Any Tissue: One-Shot Reference Guided Training-Free Automatic Point Prompting for Medical Image Segmentation (MedIA), 2025. (SCI Q1-TOP)
• [3] Xueyu Liu, Rui Wang, Yexin Lai, Guangze Shi, Feixue Shao, Fang Hao, Jianan Zhang, Jia Shen, Yongfei Wu*, Wen Zheng. Plug-and-Play PPO: An Adaptive Point Prompt Optimizer Making SAM Greater. Conference on Computer Vision and Pattern Recognition (CVPR), 2025. (CCF A)
• [4] Jia Shen, Jun Zhang, Xueyu Liu*, Yunfei Zhang, Guangze Shi, Fiexue Shao, Hangbei Cheng, Yongfei Wu*. Fourier Transform-Based Shape Constrained Framework for Generalizable Medical Image Segmentation, Chinese Conference on Pattern Recognition and Computer Vision (PRCV), 2025. (CCF C)

2024:

• [1] Xueyu Liu, Guangze Shi, Rui Wang, Yexin Lai, Jianan Zhang, Lele Sun, Quan Yang, Yongfei Wu*, MIng Li, Weixia Han, Wen Zheng. Feature-prompting GBMSeg: One-Shot Reference Guided Training-Free Prompt Engineering for Glomerular Basement Membrane Segmentation. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2024. (CCF B)
• [2] Zihao Mi, Xueyu Liu, Jianan Zhang, Guangze Shi, Yidi Li, Yongfei Wu*. Multi-instance Curriculum Learning for Histopathology Image Classifications with Hard Negative Mining and Positive Augmentation. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2024. (CCF B)

  2022:

• [1] Xueyu Liu, Ming Li, Yongfei Wu*, Yilin Chen, Fang Hao, Daoxiang Zhou, Chen Wang, Chuanfeng Ma, Guangze Shi, Xiaoshuang Zhou. An efficient glomerular object locator for renal whole slide images using proposal-free network and dynamic scale evaluation method. AI Communications, 2022. (SCI Q4)

🎖 Certifications and Awards

• “Huawei Cup” The 22th China Post-Graduate Mathematical Contest in Modeling, 2025, National Third Prize.
• 12th “Challenge Cup” China College Students Entrepreneurship Competition, 2020, National Second Prize.