牟玮 教授、博士生导师，国家级青年人才
医学科学与工程学院
北航教师个人主页：https://shi.buaa.edu.cn/muwei/zh_CN/index.htmCN/index.htm
电子邮箱：weimu@buaa.edu.cn
【教育背景】
2011.09 - 2016.07 中国科学院自动化研究所，模式识别与智能系统，工学博士
2007.09 - 2011.07 华中科技大学，测控技术与仪器，工学学士
【工作经历】
2023.01 - 至今 北京航空航天大学, 医学科学与工程学院, 教授
2022.03 - 2022.12 北京航空航天大学, 医学科学与工程学院, 副教授
2020.12 - 2021.07 美国墨菲特癌症研究中心，研究员
2016.12 - 2020.12 美国墨菲特癌症研究中心，博士后
【研究领域】
从事AI4science的相关工作，围绕癌症的诊疗决策，开展跨尺度医学数据智能感知技术及其应用研究，研发可穿戴成像芯片、病理图像及医学影像人工智能分析算法等，相关成果以在Nature Communications (ESI高被引), Cancer Research, Radiology: Artificial Intelligence,等信息与医学领域权威期刊、NeurIPS等人工智能领域顶级会议发表论文30余篇。指导本科生竞赛方面获得第十九届“挑战杯”竞赛2024年度“揭榜挂帅”专项赛擂主（全国第一）。
主持并参与国自然优秀青年、面上项目、北自然重点、科技部国家重点研发计划等，获美国国家癌症研究所青年学者奖、青岛市青年科技奖等多项国内外奖项，任中华医学会核医学分会大数据与人工智能工作委员会副主任委员等。
【代表性科研项目】
1. 国家自然科学基金，优秀青年科学基金项目，肺癌多模态医学影像分析，2023.1-2025.12，在研, 主持。
2. 国家自然科学基金，面上项目，基于影像、病理联合空间转录组多模态数据的肺癌免疫治疗原发性耐药预测关键技术研究，2026.1-2029.12，在研, 主持。
3. 国家自然科学基金委员会, 面上项目,基于PET/CT解析多分子标志物与临床事件的晚期肺癌免疫治疗预后评估, 2022.01- 2025.12, 在研, 主持。
4. 北京市自然科学基金-海淀原始创新联合基金重点项目， 基于多组学的多维立体肺癌早期筛查体系建立及应用研究，2023.1-2025.12，在研，课题负责人。
5. 国家重点研发计划，多癌联筛早诊新体系的建立和全国推广应用新策略的评价，2022.11-2025.12，在研，课题骨干。
6. 国家自然科学基金，重点项目，跨尺度融合肺癌影像、病理与微环境分子特征智能评估新辅助免疫治疗疗效的研究，2023.1-2026.12，在研，课题骨干。
7. 山东省自然科学基金，基于多任务及多模态互相关的晚期肺癌免疫治疗预后评估方法研究，2025.1-2027.12，在研，主持。
【代表性论著】
[1] Yichen Jin*, Wei Mu*, Yezhen Shi*, Qingyi Qi*, Wenxiang Wang*, Yue He*, Xiaoran Sun, Bo Yang, Peng Cui, Chengcheng Li, Fang Liu, Yuxia Liu, Guoqiang Wang, Jing Zhao, Yuzi Zhang, Shuaitong Zhang, Caifang Cao, Chao Sun, Nan Hong, Shangli Cai#, Jie Tian#, Fan Yang#, Kezhong Chen#, Development and Validation of an Integrated System for Lung Cancer Screening and Post-screening Pulmonary Nodules Management: A Proof-of-concept Study (ASCEND-LUNG), EClinicaMedicine, 75: 102769, 2024.
[2] Junjie Zhou, WEI SHAO, Yagao Yue, Wei Mu, Peng Wan, Qi Zhu, Daoqiang Zhang, MAPLE: Multi-scale Attribute-enhanced Prompt Learning for Few-shot Whole Slide Image Classification, NeurIPS 2025.
[3] Penghua Zhai†, Weixin Xu†, Guifang Duan†, Yukun Wu, Mingxin Qi, Lingqian Chang*, Wei Mu* , Artificial intelligence-integrated wearable biomedical devices for cancer management, Journal of the National Cancer Center, 2025.
[4] Shanshan Li#, Yao Fu#, Shuangshuang Ma#, Fang Shi, Lingfei Liu, Jia liu, Zengzhen wang, Yuanyuan Yan*, Wei Mu*, Imaging biomarkers related to tumor-associated macrophage in immunotherapy treatment planning for non-small cell lung cancer, Translational Lung Cancer Research, 2025.
[5] Weixin Xu, Penghua Zhai, Jie Tian* and Wei Mu*，IFRFNet: Iterative Frequency Restoration-Fusion Network for Fast System Matrix Calibration on Magnetic Particle Image, MICCAI, Cham: Springer Nature Switzerland, 2025, 290-300. (CCF B)
[6] Weixin Xu#, Penghua Zhai#, Zhongwei Bian#, Yao Fu, Yunkun Wu, Chaojuan Yang*, Jie Tian* and Wei Mu*，Rethinking the Fourier Transform: Frequency Split-Enhance Network for Fast System Matrix Calibration in Magnetic Particle Image, IEEE Transactions on Instrumentation & Measurement, 2025, 74:1-12.
[7] Yuqiong Wang#, Kuan Yang#, Zhaocun Huang#, Yusen Wang#, Ao Xiao, Xinran Jiang, Feng Liu, Zixiang Wang, Hong Sun, Yongyan Hu, Yibo Wang, Han Wu, Long Lin, Zhiyuan Jin, Lamei Du, Jiazheng Sun, Jiaqi Liu, Dedong Yin, Shenshen Kong, Kun Song, Xing Chen, Mingzhu Yang, Wei Mu*, Zhaojian Liu*, Xinge Yu, Lingqian Chang*，Efficient, High-Quality Engineering of Therapeutic Extracellular Vesicles on an Integrated Nanoplatform, ACS Nano, 2024, https://doi.org/10.1021/acsnano.4c04730.
[8] Ao Xiao#, Xinran Jiang#, Yongyan Hu#, Hu Li#, Yanli Jiao#, Dedong Yin, Yuqiong Wang, Hong Sun, Han Wu, Long Lin, Tianrui Chang, Feng Liu, Kuan Yang, Zhaocun Huang, Yanan Sun, Penghua Zhai, Yao Fu, Shenshen Kong, Wei Mu*, Yi Wang*, Xinge Yu*, Lingqian Chang*，A Degradable Bioelectronic Scaffold for Localized Cell Transfection toward Enhancing Wound Healing in a 3D Space，Advanced Material, 2024, 2404534.
[9] Shengyun Huang#, Caifang Cao#, Linna Guo, Chengze Li, Feng Zhang, Yiluo Li, Ying Liang,* Wei Mu*, Comparison of the variability and diagnostic efficacy of respiratory-gated PET/CT based radiomics features with ungated PET/CT in lung lesions，Lung cancer, 194, 107889, 2024.
[10] Yihang Tong#, Yu Zeng#, Yinuo Lu#, Yemei Huang#, Zhiyuan Jin, Zhiying Wang, YusenWang, Xuelei Zang, Lingqian Chang*, Wei Mu*, Xinying Xue*, Zaizai Dong*, Deep learning - enhanced microwell array biochip for rapid and precise quantification of Cryptococcus subtypes, VIEW, 2024, 5, 20240032.
[11] Nenghao Jin; Yu An; yu Tian; Zeyu Zhang, Kumshan He, chongwei chi, Wei Mu*; Jie Tian*; Yang Du*, Multispectral fluorescence imaging of EGFR and PD-L1 for precision detection of oral squamous cell carcinoma: A preclinical and clinical study, BMC Medicine, 22 (1), 342, 2024.
[12] Wei Mu; Lei Jiang; Jianyuan Zhang; Yu Shi; Jhanelle E Gray; Ilke Tunali; Chao Gao; Yingyi ng Sun; Jie Tian; Xinming Zhao; Xilin Sun; Robert J Gillies; Matthew B Schabath ; Non-invasive decision support for NSCLC treatment using PET/CT Radiomics, Nature Communications, 2020, 11: 5228. (SCI IF: 14.919)
[13] Wei Mu; Ilke Tunali; Jhanelle E. Gray; Jin Qi; Matthew B. Schabath; Robert J. Gillies ; Radiomics of 18F-FDG PET/CT images predicts clinical benefit of advanced NSCLC patients to checkpoint blockade immunotherapy, European Journal of Nuclear Medicine and Molecular Imaging, 2020, 47(5): 1168-1182. (SCI IF: 9.236)
[14] Wei Mu; Lei Jiang; Yu Shi; Ilke Tunali; Jhanelle E. Gray; Evangelia Katsoulakis; Jie Tian; Robert J. Gillies; Matthew B. Schabath ; Non-invasive measurement of PD-L1 status and prediction of immunotherapy response using deep learning of PET/CT images, Journal for ImmunoTherapy of Cancer, 2021, 9(6): e002118. (SCI IF: 13.751)
[15] Wei Mu; Matthew B. Schabath; Robert J. Gillies; Images are Data: Challenges and opportunities in the clinical translation of Radiomics, Cancer Research, 2022. (SCI IF: 12.701)
[16] Wei Mu; Ilke Tunali; Jin Qi; Matthew B. Schabath; Robert James Gillies ; Radiomics of 18F-Fluorodeoxyglucose PET/CT Images Predicts Severe Immune-related Adverse Events in Patients with NSCLC, Radiology: Artificial Intelligence, 2020, 2(1): e190063. (SCI IF: 13.2)
[17] Wei Mu; Chang Liu; Feng Gao; Yafei Qi; Hong Lu; Zaiyi Liu; Xianyi Zhang; Xiaoli Cai; Ruo Yun Ji; Yang Hou; Jie Tian; Yu Shi ; Prediction of clinically relevant Pancreatico-enteric Anastomotic Fistulas after Pancreatoduodenectomy using deep learning of Preoperative Computed Tomography, Theranostics, 2020, 10(21): 9779-9788. (SCI IF: 11.556)
[18] Wei Mu; Ying Liang; Lawrence O Hall; Yan Tan; Yoganand Balagurunathan; Robert Wenham; Ning Wu; Jie Tian; Robert J. Gillies ; 18F-PET/CT habitat radiomics predicts outcome of cervical cancer patients treated with chemoradiotherapy, Radiology: Artificial Intelligence, 2020, 2(6): e190218. (SCI IF: 13.2)
[19] Bruna V. Jardim-Perassi#; Wei Mu#; Suning Huang; Michal R. Tomaszewski; Jan Poleszczuk; Mahmoud A. Abdalah; Mikalai M. Budzevich; William Dominguez-Viqueira; Damon R. Reed; Marilyn M. Bui; Joseph O. Johnson; Gary V. Martinez; Robert J. Gillies ; Deep-learning and MR images to target hypoxic habitats with evofosfamide in preclinical models of sarcoma, Theranostics, 2021, 11(11): 5313-5329. (SCI IF: 11.556)
