· Personal Profile
Wei Mu, Ph.D. Professor of School of Medical Science and Engineering, Beihang University. Granted by National Natural Science Foundation of China (NSFC) Excellent Young Scientist. Ranked among the Top 2% of Scientists Worldwide (2023 - 2025). Long-term research focus on the intersection of medical imaging and artificial intelligence, with deep interdisciplinary work in medical-engineering integration for diagnosis and treatment decision-making in lung cancer, cervical cancer, glioma, and other malignancies based on multimodal imaging analysis. Has published 40+ papers as first author in authoritative journals across information science and medicine, including Nature Communications, Advanced Materials, Cancer Research, Journal for ImmunoTherapy of Cancer, and European Journal of Nuclear Medicine. Leads and participates in projects funded by the NSFC Excellent Young Scientists Fund, General Program, Beijing Natural Science Foundation Key Projects, and the National Key R&D Program of the Ministry of Science and Technology. Recipient of the Young Scientist Award from the U.S. National Cancer Institute and multiple other international honors. Serves as Standing Committee Member of the Precision Medicine and Tumor Rehabilitation Committee of the China Rehabilitation Technology Transformation and Development Promotion Association, and as Deputy Head of the Big Data and Artificial Intelligence Working Committee of the Nuclear Medicine Branch of the Chinese Medical Association.
Education
2011.09 - 2016.07 Ph.D. in Pattern Recognition and Intelligent Systems, Institute of Automation, Chinese Academy of Sciences
2007.09 - 2011.07 B.Eng. in Measurement & Control Technology and Instrumentation, Department of Control Science and Engineering, Huazhong University of Science and Technology
Professional Experience
2023.01 – Present | Professor, School of Engineering Medicine, Beihang University
2022.03 – 2022.12 | Associate Professor, School of Engineering Medicine, Beihang University
2020.12 – 2021.07 | Research Scientist, Moffitt Cancer Center, USA
2016.12 – 2020.12 | Postdoctoral Fellow, Moffitt Cancer Center, USA
Research Interests
Multimodal medical image analysis, artificial intelligence, pattern recognition, deep learning, and related interdisciplinary fields
Research Projects
NSFC Excellent Young Scientists Fund — Multimodal Medical Image Analysis of Lung Cancer | 2023–2025 | ¥2,000,000 | PI
NSFC General Program (62571019) — Key Technologies for Predicting Primary Resistance to Immunotherapy in Lung Cancer Based on Multimodal Data from Imaging, Pathology, and Spatial Transcriptomics | 2026–2029 | ¥500,000 | PI
NSFC General Program (62176013) — Prognosis Assessment of Advanced NSCLC Immunotherapy Based on PET/CT Analysis of Multi-molecular Biomarkers and Clinical Events | 2022–2025 | ¥530,000 | PI
National Key R&D Program, Ministry of Science and Technology — Establishment of a New Multi-Cancer Screening and Early Diagnosis System and Evaluation of New Strategies for Nationwide Implementation | 2022–2025 | ¥30,000,000 (PI of sub-task, ¥1,150,000)
Beijing Natural Science Foundation – Haidian Original Innovation Joint Fund Key Project — Establishment and Application of a Multidimensional Lung Cancer Early Screening System Based on Multi-omics | 2023–2025 | ¥1,000,000 (Sub-task PI, ¥150,000)
NIH R01 (CA143062-02) — Radiomics of NSCLC | 2016–2020 | $3,403,500 | Core Investigator (Completed)
Representative Publications
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
Yukun Wu#, Hao Xu #, Fan Yang*, Jie Tian *, Wei Mu*, Jian Zhou*, ASO Author Reflections: Artificial Intelligence–Driven Thoracoscopic Video Analysis for Intraoperative Visceral Pleural Invasion Prediction, Annals of Surgical Oncology, 2026, 33:3226–3227.
Chenyu Zhao#, Ao Xiao#, Chen Chen, Wei Mu*, Wen-Yang Li*, Lingqian Chang*, Nanotechnology for diagnosis and therapy of idiopathic pulmonary fibrosis: recent advances and future perspectives, Nano Today, 2026, 66, 102889
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
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
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
Zhaocun Huang, Feng Liu, Deyuan Zhi, Bing Liu, Yihang Tong, Chao Lv, Xi Chen, Shi Yan, Chengbao Wu, Wei Mu*, Nan Wu*, Lingqian Chang*, Zaizai Dong*, Nano-Electro-Sampling and Intelligent Analysis System for Real-Time Gene Profiling of Living Cells, Small, 2025, e06688
Long Cheng†, Zhiying Wang†, Chengbao Wu†, Feng Liu, Hui Li, Yunke Feng, Xi Chen*, Xinxin Hang, Yu Zeng, Wei Mu*, Yuhao Zhou, Liye Liu, Lingqian Chang*, Qiaowei Liu*, Yi Hu*, Yang Wang*†, An Integrated Electrolysis-Enrichment Microchip for Ultra-Rapid and Sensitive mRNA Detection, Research, 2025
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
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)
Yihang Tong#, Zinan Zhao#, Penghua Zhai#,Yu Zeng#, Han Wu#, Jiajie Shi，Fan Wang, Liu Wang*, Xiaolan Zhong*, Wei Mu* , Lingqian Chang*,From Individual Modalities to Multi-Physical Synergy: Implantable Electronic, Photonic, Magnetic Platforms for the Treatment of Internal Organ Disease，Applied Physics Reviews, 2025
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, 18, 47, 32421–32437
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 Materials, 2024, 2404534
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
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, https://doi.org/10.1002/VIW.2024003
Feng Liu#, Rongtai Su#, Siqi Wang#, Wei Mu*, Lingqian Chang*, Advanced Micro/Nano-Electroporation for Gene Therapy: Recent Advances and Future Outlook. Nanoscale, 2024, DOI: 10.1039/D4NR01408A
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
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
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)
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)
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)
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)
Wei Mu; Evangelia Katsoulakis; Christopher J. Whelan; Kenneth L. Gage; Matthew B. Schabath; Robert J. Gillies ; Radiomics predicts risk of cachexia in advanced NSCLC patients treated with immune checkpoint inhibitors, British Journal of Cancer, 2021, 125: 229-239 (SCI IF: 7.64)
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
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) (SCI IF: 11.556)
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
Wei Mu; Zhe Chen; Xiaoqian Dai; Jie Tian ; Noninvasive Estimation of the Input Function for Dynamic Mouse F-18-FDG MicroPET Studies, IEEE Transactions on Biomedical Engineering, 2013, 60(11): 3103-3112 (SCI IF: 4.538)
Wei Mu; Zhe Chen; Wei Shen; Feng Yang; Ying Liang; Ruwei Dai; Ning Wu; Jie Tian ; A Segmentation Algorithm for Quantitative Analysis of Heterogeneous Tumors of the Cervix With F-18-FDG PET/CT, IEEE Transactions on Biomedical Engineering, 2015, 62(10): 2465-2479 (SCI IF: 4.538)
Wei Mu; Zhe Chen; Ying Liang; Wei Shen; Feng Yang; Ruwei Dai; Ning Wu; Jie Tian ; Staging of cervical cancer based on tumor heterogeneity characterized by texture features on F-18-FDG PET images, Physics in Medicine and Biology, 2015, 60(13): 5123-5139 (SCI IF: 3.609)
Fei Kang#; Wei Mu#; Jie Gong#; Shengjun Wang; Guoquan Li; Guiyu Li; Wei Qin; Jie Tian; Jing Wang ; Integrating manual diagnosis into radiomics for reducing the false positive rate of 18F-FDG PET/CT diagnosis in patients with suspected lung cancer, European journal of medicine and molecular imaging, 2019, 46(13): 2770-2779 (SCI IF: 9.236)
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)
Sandy Napel; Wei Mu; Bruna V. Jardim‐Perassi; Hugo J. W. L. Aerts; Robert J. Gillies ; Quantitative imaging of cancer in the postgenomic era: Radio(geno)mics, deep learning, and habitats, Cancer, 2018, 124(24): 4633-4649 (SCI IF: 6.86)
Panwen Tian#; Bingxi He#; Wei Mu#; Kunqin Liu; Li Liu; Hao Zeng; Yujie Liu; Lili Jiang; Ping Zhou; Zhipei Huang; Di Dong; Weimin Li ; Assessing PD-L1 expression in non-small cell lung cancer and predicting responses to immune checkpoint inhibitors using deep learning on computed tomography images, Theranostics, 2021, 11(5): 2098-2107 (SCI IF: 11.556)
Student Competition Mentorship
19th "Challenge Cup" National Competition (2024) — "Open Bidding" Special Track: AI-based Myopia Risk Prediction Technology and Frontier Research — National Champion (1st Place)
Award
(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
Invited talk
(1) Wei Mu; Radiomics and AI-based treatment decision support for non-small cell lung cancer (invited talk), AACR Virtual Special Conference: Artificial Intelligence, Diagnosis, and Imaging, Virtual meeting, United States, 2021-1-13
(2) Wei Mu ; Radiomics and AI-based treatment decision support for non-small cell lung cancer (invited talk), Quantitative Imaging Network Annual Meeting, Virtual meeting, United States, 2021-1-22