牟玮，国家高层次青年人才，入选2023-2026全球前2％顶尖科学家榜单，多年来一直从事医学影像与人工智能交叉学科研究，围绕肺癌、宫颈癌和胶质瘤等癌症的诊疗决策，在PET/CT，MRI，病理图像等多模态影像分析方面开展了深入的医工交叉研究。以第一作者在Nature Sensors，Nature Communications, Advanced Materials, Cancer Research,  Journal for Immunotherapy of Cancer,  European Journal of Nuclear Medicine，TMI等信息与医学领域权威期刊发表论文40余篇。主持并参与国自然优秀青年项目（海外）、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等多项国际奖项，任中华医学会核医学分会大数据与人工智能工专委会副主任委员、MICS委员会委员、MMR青年编委等。

教育经历

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   华中科技大学控制科学与工程系，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

研究方向

多模态医学图像分析、人工智能、模式识别、深度学习等多学科交叉

本科生竞赛指导

第十九届“挑战杯”竞赛2024年度“揭榜挂帅”专项赛，《基于人工智能的近视风险预测技术和前沿研究》，擂主（全国第一）

首届北京市大学生“人工智能+”创新大赛，一等奖

学术奖励

(1) Wei Mu; Laurence P. Clarke Young Scientist Award, The Quantitative Imaging Network o f the National Cancer Institute, National Institutes of Health, 2021

(2) Wei Mu; Young Investigator of the Year Runner-Up Award, World Molecular Imaging Congress,  2020

(3) Wei Mu; Women in Molecular Imaging Network Scholar Award, World Molecular Imaging Congress,  2020

(4)青岛市青年科技奖，2025

代表性论著

[1] Yao Fu#, Xin-Yun Huang#, Yue Wang#, Fanghu Wang#, Shanshan Li#, Chong Jiang, Yujing Zhou, Rui Guo, Lei Jiang, Yinuo Lu, Yukun Wu, Mingxin Qi, Ziwei Gao, Jie Tian*, Xin Li*, Wei Mu*, Biao Li*, LymRadar: Artificial Intelligence-driven Multimodal Risk Prediction for Diffuse Large B-cell Lymphoma across Multicenter cohorts，Nature Communications, 2026, Accepted 

[2] Xinran Jiang#, Yongcun Hao#, Yanli Jiao#, Yuqiong Wang, Han Wu, Kuanming Yao, Zhuoming Zhao, Fuqi Yao, Yihang Tong, Shengda Cao, Honglong Chang, Dedong Yin*, Zhou Chen*, Wei Mu*, Lingqian Chang*, Fabrication and use of implantable, battery-free nanofluidic patch architectures for intracellular electro-delivery in vivo, Nature Protocols, 2026, accepted. 

[3] Yinuo Lu#, Mingxin Qi#, Yao Fu, Zhuoran Xiao, Wei Shao*, Jie Tian*, and Wei Mu*，StableMIL: Entropy-Stabilized Attention-based Multiple Instance Learning for Morphologically Variable Whole Slide Images, IEEE Transactions on Medical Imaging, 2026, 45(7): 3649-664

[4] Mingxin Qi, Hongyu Li, Yinuo Lu, Wei Mu*, GFR-MIL: Glance - Focus - Reflect Based Multiple Instance Learning for Multi-Scale Whole Slide Image Analysis, MICCAI 2026.

[5] Yao Fu#, Ziwei Gao#, Yinuo Lu#, Weixin Xu, Mingxin Qi, Yukun Wu, Wei Mu*, TCFD-Net: Temporal-Calibrated Feature Disentanglement Network for Dual-timepoint CT-based Immunotherapy Response Prediction in Advanced Non-small Cell Lung Cancer, MICCAI 2026.

[6] Yukun Wu#, Hao Xu #, Xinghua Cheng, Pengchong Li, Jiantao Li, Ruiheng Jiang, Fengwei Li, Songjing Zhao, Yuxuan Wang, Shenrui Zhang, Zewen Sun, Sida Cheng, Tian Guan, Hao Li, Xiuyuan Chen, Feng Yang, Guanchao Jiang, Shanshan Li, Jun Wang, Yun Li, Fan Yang *, Jie Tian *, Wei Mu*, Jian Zhou*, Development and Validation of an Artificial Intelligence Surgical Video Analysis Model for Predicting Visceral Pleural Invasion in Lung Cancer Surgery: A Multicenter Study, Annals of Surgical Oncology, 2026, 33(4), 3138-3150, 2026

[7] 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, 2025，5(6): 561-576.

[8] 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

[9] 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)

[10] 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

[11] 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) 

[12] 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) 

[13] 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) 

[14] 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) 

[15] 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 

[16] 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