周少华
讲席教授
邮件：skevinzhou@ustc.edu.cn
所属单位：生物医学工程学院
主要研究方向：AI for Medicine（群体健康；医学文本、影像、病理、组学分析）, AI for Science （RNA建模）
本科毕业于中国科学技术大学，博士毕业于美国马里兰大学，曾任西门子高级研发总监及首席AI专家。现任中国科学技术大学讲席教授，博导，生物医学工程学院执行院长，医学影像智能与机器人研究中心主任，江苏省多模态数字孪生技术重点实验室。Fellow of AIMBE (美国医学与生物工程院)、IAMBE（国际医学与生物工程科学院）、IEEE（电气与电子工程师协会）、MICCAI（医学影像计算与计算机辅助介入国际协会）、NAI（美国国家发明家科学院）。
部分学术论文和公开出版的著作 ：
- 累计撰编专著10本、发表400余篇论文
- 论文列表https://scholar.google.com/citations?user=8eNm2GMAAAAJ
[1] S Kevin Zhou, Hayit Greenspan, and Dinggang Shen (Eds.), Deep Learning for Medical Image Analysis (2nd edition), Academic Press, 2023. (ISBN 9780323851244. MICCAI book series. 518 pages, 专著)
[2] S Kevin Zhou, Daniel Rueckert, and Gabor Fichtinger (Eds.) Handbook of Medical Image Computing and Computer Assisted Intervention, Elsevier/Academic Press, 2019. (ISBN 9780128161760. MICCAI book series. 1072 pages, 专著)
[3] S Kevin Zhou, H Greenspan, C Davatzikos, JS Duncan, B van Ginneken, A Madabhushi, JL Prince, D Rueckert, and RM Summers. A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises. Proceedings of the IEEE, 109(5):820-838, May 2021. (247 reference, 综述)
[4] Yujia Li, H Li, Z Xu, and S Kevin Zhou. CLIS: Causality-inspired longitudinal image synthesis and its application to Alzheimer’s disease characterization. Medical Image Analysis, 2026. (期刊)
[5] Rui Yan, X Zhang, Z Jiang, B Wang, X Bian, F Ren, and S Kevin Zhou. Pathway-aware multimodal transformer (PAMT): Integrating pathological image and gene expression for interpretable cancer survival analysis. IEEE Trans. on Pattern Analysis and Machine Intelligence, 2025. (期刊)
[6] Rongsheng Wang, Q Yao, Z Jiang, H Lai, Z He, X Tao and S Kevin Zhou. ECAMP: Entity-centered context-aware medical vision language pre-training. Medical Image Analysis, 103690, 2025. (期刊)
[7] Heqin Zhu, F Tang, Q Quan, K Chen, P Xiong, and S Kevin Zhou. Deep generalizable prediction of RNA secondary structure via base pair motif energy. Nature Communications, 2025. (期刊)
[8] Zexiang Li, S Kevin Zhou. When modalities compete: Modality-aware optimization on low-rank manifolds. ACM Multimedia (ACMMM), 2026. (CCF-A会议)
[9] Xinpei Gao, X Luo, M Liu, C Wang, and S Kevin Zhou. AD-BTS: Adaptive dual-branch token sparsification via spatial information density. ICML 2026. (CCF-A会议)
[10] Rongge Mao, C Dong, and S Kevin Zhou. LazyVAR: Accelerating visual autoregressive models via scale-wise token pruning and parallel group decoding. CVPR 2026. (CCF-A会议)
[11] Xueming Fu, F Tang, R Wang, Y Li, L Han, J Lu, Z Jiang, and S Kevin Zhou. MedGMAE: Gaussian masked autoencoders for medical volumetric representation learning. ICLR 2026. (CCF-A会议)
[12] Yuan Feng, J Lv, Y Cao, X Xie, S Kevin Zhou. Ada-KV: Optimizing KV cache eviction by adaptive budget allocation for efficient LLM inference. NeurIPS, 2025. (CCF-A会议)