持续招收2023级硕士生, 请发邮件附送简历联系 shaowei20022005@nuaa.edu.cn

南京航空航天大学计算机科学与技术学院副教授，2018年博士毕业于南京航空航天大学师从张道强教授，2019年至2021年在美国印第安纳大学医学院从事博士后研究，师从Kun Huang教授。主要研究方向为机器学习以及医学图像处理，目前以第一作者，通讯作者发表论文30余篇，相关工作发表在Nature Communications, NPJ Precision Oncology，Cell Reports, IEEE TMI, MedIA, Bioinformatics, IEEE TCBB等国际一流期刊。 荣获医学图像处理国际顶级会议MICCAI 2019 青年科学家奖(全球5人，中国大陆唯一)，指导学生再获MICCAI 2022 青年科学家奖，入选2020年度南京航空航天大学长空之星。

部分期刊论文：

  1) Du, J., Zhang, J., Wang, L., Wang, X., Zhao, Y., Lu, J., Fan, T., Niu, M., Zhang, J., Cheng, F. Li, J., Shao, W*  and  Sheng, J. Selective oxidative protection leads to tissue topological changes orchestrated by macrophage during ulcerative colitis. Nature Communications, 14(1), p.3675, 2023. (通讯作者)

  2) Zhang, J., Song, J., Tang, S., Zhao, Y., Wang, L., Luo, Y., Tang, J., Ji, Y., Wang, X., Li, T.， Zhang, H.,  Shao, W*.,  Sheng, J., Liang, T and Bai, X. Multi-omics analysis reveals the chemoresistance mechanism of proliferating tissue-resident macrophages in PDAC via metabolic adaptation. Cell Reports, 42(6),  2023. (通讯作者)

  3) Shao W, Zuo Y, Shi Y, Wu Y, Tang J, Zhao J, Sun L, Lu Z, Sheng J, Zhu Q, Zhang D. Characterizing the Survival-Associated Interactions between Tumor-infiltrating Lymphocytes and Tumors from Pathological Images and Multi-omics Data. IEEE Transactions on Medical Imaging. 2023 May 9.

  4) Shao W,  Liu J, Zuo Y, Qi S, Hong H, Sheng J, Zhu Q, Zhang D. FAM3L: Feature-Aware Multi-modal Metric Learning for Integrative Survival Analysis of Human Cancers. IEEE Transactions on Medical Imaging. 2023 Mar 27.

  5）Shao, W., Han, Z., Cheng, J., Cheng, L., Wang, T., Sun, L., Lu, Z., Zhang, J., Zhang, D. and Huang, K*.,. Integrative analysis of pathological images and multi-dimensional genomic data for early-stage cancer prognosis. IEEE Transactions on Medical Imaging, 39(1), 99-110,2020. 

  6）Shao, W., Wang, T., Huang, Z., Han, Z., Zhang, J. and Huang, K., Weakly supervised deep ordinal cox model for survival prediction from whole-slide pathological images. IEEE Transactions on Medical Imaging, 40(12), 3739-3747,2021   

  7) Shao, W., Wang, T., Sun, L., Dong, T., Han, Z., Huang, Z., Zhang, J., Zhang, D. and Huang, K. Multi-task multi-modal learning for joint diagnosis and prognosis of human cancers. Medical Image Analysis, 65:101795, 2020

  8）Wang, T*., Shao, W*., Huang, Z., Tang, H., Zhang, J., Ding, Z. and Huang, K. MOGONET integrates multi-omics data using graph convolutional networks allowing patient classification and biomarker identification. Nature Communications, 12(1), pp.1-13，2021 (共同第一作者) 

  9) Huang, Z., Shao, W*., Han, Z., Alkashash, A.M., De la Sancha, C., Parwani, A.V., Nitta, H., Hou, Y., Wang, T., Salama, P. and Rizkalla, M., 2023. Artificial intelligence reveals features associated with breast cancer neoadjuvant chemotherapy responses from multi-stain histopathologic images. NPJ Precision Oncology, 7(1), pp.14-21(共同第一作者)

  10) Zhu, Q., Xu, B., Huang, J., Wang, H., Xu, R., Shao,W* and Zhang,D. Deep Multi-Modal Discriminative and Interpretability Network for Alzheimer’s Disease Diagnosis. IEEE Transactions on Medical Imaging. in press, pp.1-13, 2022(通讯作者)

  11）Zhu, Q., Wang, H., Xu, B., Zhang, Z., Shao, W* and Zhang, D. Multimodal Triplet Attention Network for Brain Disease Diagnosis. IEEE Transactions on Medical Imaging, 41(12), 2022，3884-3894（通讯作者）.

  12）Shao, W., Huang, S.J., Liu, M. and Zhang, D.  Querying Representative and Informative Super-pixels for Filament Segmentation in Bioimages.  IEEE  Transactions on Computational Biology and Bioinformatics, 17(4),  1394-1405,   2019 

    13) Shao, W., Liu, M. and Zhang, D*., Human cell structure-driven model construction for predicting protein subcellular location from biological images. Bioinformatics, 32(1), pp.114-121, 2016

  14)Shao, W., Liu, M., Xu, Y.Y., Shen, H.B. and Zhang, D.*. An organelle   correlation-guided feature selection approach for classifying multi-label subcellular bio-images. IEEE/ACM Transactions on Computational Biology and   Bioinformatics, 15(3), pp.828-838, 2017

 

部分会议论文：

1）Zuo, Y., Wu, Y., Lu, Z., Zhu, Q., Huang, K., Zhang, D. and Shao, W*. Identify Consistent Imaging Genomic Biomarkers for Characterizing the Survival-Associated Interactions Between Tumor-Infiltrating Lymphocytes and Tumors. In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2022),222-231, 2022(指导学生获医学图像分析国际顶级会议MICCAI 2022青年科学家奖，全球共5人，通讯作者)

2）Shao, W., Wang, T., Huang, Z., Cheng, J., Han, Z., Zhang, D. and Huang, K*. Diagnosis-Guided Multi-modal Feature Selection for Prognosis Prediction of Lung Squamous Cell Carcinoma. In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2019), 113-121. 2019.（荣获医学图像分析国际顶级会议MICCAI 2019青年科学家奖，国内唯一，全球共5人）

3) Shao, W., Cheng, J., Sun, L., Han, Z., Feng, Q., Zhang, D. and Huang, K*., Ordinal multi-modal feature selection for survival analysis of early-stage renal cancer. In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2018), 648-656, 2018. 

4) Liu, Z, Shao W, Zhang J, Zhang M, and Huang K. Transfer Learning via Optimal Transportation for Integrative Cancer Patient Stratification. In International Joint Conference on Artificial Intelligence (IJCAI 2021), 221-227, 2021