教师主页移动版

个人经历 personal experience 工作经历 教育经历 2016.03 - 至今         西北工业大学自动化学院  助理教授、长聘副教授2020.07 - 至今         西北工业大学自动化学院  博士生导师2018.07 - 至今         西北工业大学自动化学院  硕士生导师2013.08 - 2016.01      美国印第安纳大学医学院  博士后 2007.09 - 2013.06      西安交通大学电信学院2003.09 - 2007.07      西北工业大学自动化学院

教育教学

教育教学 Education and teaching 招生信息 每年招收：  博士研究生：1-2名           硕士研究生：2-3名欢迎自动化、计算机科学与技术、生物医学工程、数学及电子信息学科的同学，尤其是对机器学习、数据挖掘、优化算法、生物信息学、医学图像分析等研究方向感兴趣的优秀同学保送/报考。课题组提供宽松的科研环境，并常年与国外合作，提供国内外交流机会。欢迎来信咨询：dulei@nwpu.edu.cn（请附上成绩单）。

荣誉获奖

团队信息 Team Information 信息融合技术教育部重点实验室成员;自动化学院郭雷、韩军伟教授团队成员;与宾夕法尼亚大学医学院和印第安纳大学医学院保持长期的密切合作。在读学生：2021级：尚沐衡（博士）、张建婷、谢强2022级：张金（博士）、刘朵朵、郭惠云、马子康2023级：杨言（博士）、李迎立、崔文瑞、庞宏毕业学生：2020级：赵颖(TMI，中国联通)、余城林（TCBB，中国电科）、崔鼎男（发明专利,西安航天动力）2019级：刘方(TMI、Bioinformatics、MICCAI，国奖、优硕，华为)、张金（Medical Image Analysis、BMC Bioinformatics、BIBM，国奖、优硕、转博）、王惠爱（SCIENCE CHINA Information Science，农发行）

科学研究

社会兼职 Social Appointments BIBM 2018 Session ChairBI 2017、 BI 2019 、BI2023 Special Session ChairBIBM 2019、BIBM 2020、BIBM 2021 、BIBM 2022、BIBM 2023 PC Member中国计算机学会生物信息学专委委员中国自动化学会智能健康与生物信息专委委员中国自动化学会人工智能科普工作委员会委员MICS委员CCF会员、CAA会员、ISCB会员、MICCAI会员、IEEE会员领域顶级期刊及会议如T-PAMI、TMI、Medical Image Analysis、Bioinformatics、Briefings in Bioinformatics、Journal of the Royal Statistical Society: Series C、TNNLS、Human Brain Mapping、Brain Imaging Behavior、TCBB、JBHI、IPMI、MICCAI、BIBM等审稿人。

学术成果

科学研究 Scientific Research 研究方向为数据挖掘与机器学习、影像遗传学(Imaging Genetics)或影像基因组学(Imaging Genomics）、生物信息学、医学图像处理、精准医学、数据流挖掘等。主持科技创新2030重点项目子课题、国家自然科学基金面上项目两项、青年项目等十余项科研项目。科研项目（主持NSFC面上项目、青年项目各一项，科技部重点研发计划，省部级项目5项）： [1] 2024-2027 国家自然科学基金面上项目 面向神经退行性疾病异质性的影像遗传学分析关键技术研究 (No. 62373306，主持)[2] 2022-2026 科技创新2030“脑科学与类脑研究”重点项目子课题 (主持)[3] 2020-2023 国家自然科学基金面上项目 基于多任务多视角的影像遗传学分析方法研究（No. 61973255，主持）[4] 2020-2021 陕西省自然科学基础研究计划面上项目 面向影像基因组学的多视角学习方法（No. 2020JM-142，主持）[5] 2020-2021 计算神经科学与类脑智能教育部重点实验室开放课题 多模态、纵向脑影像基因组学计算方法研究 （主持）[6] 2017-2019 国家自然科学基金青年项目 影像遗传学中海量数据挖掘算法研究及其在老年痴呆症中的应用（No. 61602384，主持）[7] 2017-2018 陕西省自然科学基础研究计划青年项目 超高维影像基因组学分析方法研究（No. 2017JQ6001，主持）[8] 2017-2018 2017年度留学回国人员科技活动项目择优资助 脑影像-全基因组关联分析中的大数据挖掘方法研究(No. 2017022，主持)[9] 2017-2018 中国博士后科学基金面上项目 影像基因组学中的高效多视角学习方法研究（No.2017M613202，主持）[10] 2017-2018 陕西省博士后科研资助项目 影像基因组学中的优化算法研究(No. 2017BSHEDZZ81，主持)[11] 2018-2019 中央高校基本科研业务费（主持）[12] 2021-2026 国家自然科学重点项目 基于深度学习的脑影像基因组学分析方法（No. 62136004，296万，主要参与）[13] 2019-2023 国家自然科学重点项目 基于脑成像的视听深度神经网络构建与应用（No. 61836006，291万，参与）[14] 2020-2024 国家自然科学重点项目 时空多尺度动态脑功能网络的深度神经网络分析方法及应用（No. 61936007，300万，参与）[15] 2022-2026 科技创新2030“脑科学与类脑研究”青年科学家项目 (500万,参与)

综合介绍

学术成果 Academic Achievements 以第一作者发表学术论文30余篇,BIBM 2018最佳论文奖 ( *通讯作者； # 共同第一作者；       指导的学生)，部分论文的代码可在https://github.com/dulei323下载使用。2024:[1] Jin Zhang, Zikang Ma, Yan Yang, Lei Guo, Lei Du*. Modeling genotype-protein interaction and correlation for Alzheimer's disease: A multi-omics imaging genetics study. Briefings in Bioinformatics (IF = 9.5, Top journal). March 2024. DOI: https://doi.org/10.1093/bib/bbae038.[2] Huiyun Guo, Minjianan Zhang, Lei Du*. A Bayesian Group Sparse Canonical Correlation Analysis Method for Brain Imaging Genomics. IEEE International Symposium on Biomedical Imaging (ISBI 2024), May 2024.2023:[1] Lei Du*, Ying Zhao, Jianting Zhang, Muheng Shang, Jin Zhang, Junwei Han. Identification of genetic risk factors based on disease progression derived from longitudinal brain imaging phenotypes. IEEE Transactions on Medical Imaging (IF = 10.6, Top journal). Oct. 2023. Accepted. DOI: 10.1109/TMI.2023.3325380.[2] Lei Du*, Jin Zhang, Ying Zhao, Muheng Shang, Lei Guo, Junwei Han. inMTSCCA: An Integrated Multi-task Sparse Canonical Correlation Analysis for Multi-omic Brain Imaging Genetics. Genomics, Proteomics & Bioinformatics, March, 2023. Accepted. (中国科技期刊卓越行动计划重点期刊, TOP Journal, IF=9.5). DOI: 10.1016/j.gpb.2023.03.005.[3] Xin Zhang, Yipeng Hao, Jin Zhang, Yanuo Ji, Shihong Zou, Shijie Zhao, Songyun Xie, Lei Du*. A Multi-task SCCA Method for Brain Imaging Genetics and its Application in Neurodegenerative Diseases. Computer Methods and Programs in Biomedicine, Volume 232, April, 2023.(IF=6.1)[4] Chenglin Yu, Shu Zhang, Muheng Shang, Lei Guo, Junwei Han, Lei Du*. A Multi-task Deep Feature Selection Method for Brain Imaging Genetics. IEEE/ACM Transactions on Computational Biology and Bioinformatics (CCF B, IF = 4.5). July, 2023, Accepted.[5] Duo Xi, Dingnan Cui, Jin Zhang, Muheng Shang, Minjianan Zhang, Lei Guo, Hunwei Han,  Lei Du*. Identification of Disease-sensitive Brain Imaging Phenotypes and Genetic Factors using GWAS Summary Statistics. The 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) (医学图像领域顶级会议, CCF B). Vancouver, Canada, October 8-12, 2023. [32% acceptance rate][6] Muheng Shang, Yan Yang, Minjianan Zhang, Jin Zhang, Duo Xi, Lei Guo, Lei Du*. Identifying Disease-related brain Imaging Quantitative Traits and Related Genetic Variations via A Bidirectional Association Learning Method. IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (CCF B). Istanbul, Turkey, December 05-08, 2023. [19.5% acceptance rate][7] Jin Zhang, Qiang Xie, Muheng Shang, Duo Xi, Minjianan Zhang, Lei Guo, Lei Du*. Identifying Main and Epistasis Effects of Genetic Variations on Neuroimaging Phenotypes Using Effective Feature Interaction Learning. IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (CCF B). Istanbul, Turkey, December 05-08, 2023. [19.5% acceptance rate] [8] Yaonai Wei, Tuo Zhang, Han Zhang, Tianyang Zhong, Lin Zhao, Zhengliang Liu, Chong Ma, Songyao Zhang, Muheng Shang, Lei Du, Xiao Li, Tianming Liu, and Junwei Han. Chat2Brain: A Method for Mapping Open-Ended Semantic Queries to Brain Activation Maps. IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (CCF B). Istanbul, Turkey, December 05-08, 2023. [19.5% acceptance rate]2022:[1] Lei Du*, Huiai Wang, Jin Zhang, Shu Zhang, Lei Guo, Junwei Han. Adaptive Structured Sparse Multiview Canonical Correlation Analysis for Multimodal Brain Imaging Association Identification. SCIENCE CHINA Information Sciences (CCF A, 中国科技期刊卓越行动计划重点期刊，IF=8.8). September, 2022, Accepted.[2] Zhibin He#, Lei Du#, Ying Huang, Xi Jiang, Jinglei Lv, Lei Guo, Shu Zhang, Tuo Zhang. Gyral hinges account for the highest cost and the highest communication capacity in a corticocortical network. Cerebral Cortex, Volume 32, Issue 16, 2022.(Top Journal, IF=4.86, 共一)[3] Jin Zhang, Huiai Wang, Ying Zhao, Lei Guo, Lei Du*. Identification of Multimodal Brain Imaging Association via A Parameter Decomposition based Sparse Multi-view Canonical Correlation Analysis Method. BMC Bioinformatics. February, 2022, Accepted.[4] Jin Zhang#, Muheng Shang#, Qiang Xie, Minjianan Zhang, Duo Xi, Lei Guo, Junwei Han, Lei Du*. A Sparse Multi-task Contrastive and Discriminative Learning Method with Feature Selection for Brain Imaging Genetics. IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (CCF B). Las Vegas, NV, USA, December 06-08, 2022. 2021:[1] Lei Du*, Jin Zhang, Fang Liu, Huiai Wang, Lei Guo, Junwei Han. Identifying Associations among Genomic, Proteomic and Imaging Biomarkers via Adaptive Sparse Multi-view Canonical Correlation Analysis. Medical Image Analysis (IF = 11.14, Top journal). accepted, Feb. 2021.[2]  Lei Du*, Kefei Liu, Xiaohui Yao, Shannon L. Risacher, Junwei Han, Andrew J. Saykin, Lei Guo, Li Shen*. Multi-Task Sparse Canonical Correlation Analysis with Application to Multi-Modal Brain Imaging Genetics. IEEE/ACM Transactions on Computational Biology and Bioinformatics (IF = 2.896, CCF B类). vol. 18, no. 1, pp. 227-239, 2021, doi: 10.1109/TCBB.2019.2947428.[3] Xin Zhang#, Yipeng Hao#, Jin Zhang, Shihong Zou, Songyun Xie, Lei Du*. Improved Multi-task SCCA for Brain Imaging Genetics via Joint Consideration of the Diagnosis, Parameter Decomposition and Network Constraints. IEEE International Conference on Bioinformatics and Biomedicine (BIBM). Virtual conference, 2021, pp. 1159-1164, doi: 10.1109/BIBM52615.2021.9669899. (CCF B类)2020:[1] Lei Du*, Fang Liu, Kefei Liu, Xiaohui Yao, Shannon L. Risacher, Junwei Han, Andrew J. Saykin, Li Shen*. Associating Multi-modal Brain Imaging Phenotypes and Genetic Risk Factors via A Dirty Multi-task Learning Method. IEEE Transactions on Medical Imaging (IF = 7.82, Top journal). vol. 39, no. 11, pp. 3416-3428, Nov. 2020, doi: 10.1109/TMI.2020.2995510.[2] Lei Du*, Fang Liu, Kefei Liu, Xiaohui Yao, Shannon L. Risacher, Junwei Han, Lei Guo, Andrew J. Saykin, Li Shen*. Identifying diagnosis-specific genotype-phenotype associations via joint multi-task sparse canonical correlation analysis and classification. Bioinformatics (IF = 5.61, Top journal). [ISMB 2020 Issue, 19.4% acceptance rate], July 1, 2020. DOI: 10.1093/bioinformatics/btaa434.[3] Lei Du*, Kefei Liu, Xiaohui Yao, Shannon L. Risacher, Junwei Han, Andrew J. Saykin, Lei Guo, Li Shen*. Detecting genetic associations with brain imaging phenotypes in Alzheimer's disease via a novel structured SCCA approach. Medical Image Analysis (IF = 11.14, Top journal). Volume 61, 101656, 2020.[4] Lei Du*, Jin Zhang, Fang Liu, Minjianan Zhang, Huiai Wang, Lei Guo, Junwei Han. Mining High-order Multimodal Brain Image Associations via Sparse Tensor Canonical Correlation Analysis. IEEE International Conference on Bioinformatics and Biomedicine (BIBM). Seoul, South Korea, December 16-19, 2020. (CCF B类)[5] Tuo Zhang, Zhibin He, Xi Jiang, Lei Guo, Xiaoping Hu, Tianming Liu,  Lei Du*. Species-Shared and -Specific Structural Connections Revealed by Dirty Multi-Task Regression. The 23rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) (医学图像领域顶级会议), Lima, Peru, October 4-8, 2020. [15% early acceptance rate]2019:[1] Lei Du*, Kefei Liu, Lei Zhu, Xiaohui Yao, Shannon L. Risacher, Lei Guo, Andrew J. Saykin, Li Shen*. Identifying progressive imaging genetic patterns via multi-task sparse canonical correlation analysis: a longitudinal study of the ADNI cohort. Bioinformatics (IF = 5.41, Top journal). [ISMB/ECCB 2019 Issue, 18.9% acceptance rate]. July, 2019. DOI: 10.1093/bioinformatics/btz320.[2] Lei Du*, Fang Liu, Kefei Liu, Xiaohui Yao, Shannon L. Risacher, Junwei Han, Lei Guo, Andrew J. Saykin, Li Shen. A dirty multi-task learning method for multi-modal brain imaging genetics. The 22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)（医学图像领域顶级会议）, Shenzhen, China, October 13-17, 2019. [31% acceptance rate][3] Lei Du*, Kefei Liu, Xiaohui Yao, Shannon L. Risacher, Lei Guo, Andrew J. Saykin, Li Shen. Diagnosis Status Guided Brain Imaging Genetics via Integrated Regression and Sparse Canonical Correlation Analysis. IEEE International Symposium on Biomedical Imaging (ISBI). Venice, Italy, April 8-11, 2019.2018:[1] Lei Du*, Kefei Liu, Xiaohui Yao, Shannon L. Risacher, Junwei Han, Lei Guo, Andrew J. Saykin, Li Shen. Fast multi-task SCCA learning with feature selection for multi-modal brain imaging genetics. IEEE International Conference on Bioinformatics and Biomedicine (BIBM). Madrid, Spain, December 3-6, 2018. (CCF B类，Best Paper Award)[2] Lei Du, Kefei Liu, Tuo Zhang, Xiaohui Yao, Jingwen Yan, Shannon L. Risacher, Junwei Han, Lei Guo, Andrew J. Saykin, Li Shen*. A Novel SCCA Approach via Truncated L1-norm and Truncated Group Lasso for Brain Imaging Genetics. Bioinformatics: 2018,34(2), pp. 278-285. (IF = 7.307, Top journal)2017:[1] Lei Du*, Kefei Liu, Xiaohui Yao, Jingwen Yan, Shannon L. Risacher, Junwei Han, Lei Guo, Andrew J. Saykin, Li Shen*. Pattern Discovery in Brain Imaging Genetics via SCCA Modeling with a Generic Non-convex Penalty. Scientific Reports: 2017.10, accepted. (IF = 4.2589)[2] Lei Du*, Tuo Zhang, Kefei Liu, Jingwen Yan, Xiaohui Yao, Shannon L. Risacher, Andrew J. Saykin, Junwei Han, Lei Guo, Li Shen*. Identifying Associations Between Brain Imaging Phenotypes and Genetic Factors via A Novel Structured SCCA Approach. The 25th Biennial International Conference on Information Processing in Medical Imaging (IPMI), Boone, USA, June 24-30, 2017 (医学图像领域顶级会议)[3] Yuming Huang, Lei Du*, Kefei Liu, Xiaohui Yao, Shannon L. Risacher, Lei Guo, Andrew J. Saykin, Li Shen. A fast SCCA algorithm for big data analysis in brain imaging genetics. MICCAI Workshop on Imaging Genetics (MICGen), 9 pages, September 10, 2017. (Corresponding author)[4] Xiao Li, Tuo Zhang, Qinglin Dong, Shu Zhang, Xintao Hu, Lei Du, Lei Guo, Tianming Liu. Predicting cortical 3-hinge locations via structural connective features. IEEE International Symposium on Biomedical Imaging (ISBI). 2017: 533-5372016:[1] Lei Du, Heng Huang, Jingwen Yan, Sungeun Kim, Shannon L. Risacher, Mark Inlow, Jason H. Moore, Andrew J. Saykin, Li Shen*. Structured Sparse Canonical Correlation Analysis for Brain Imaging Genetics: An Improved GraphNet Method. Bioinformatics: 2016, 32(10), pp.1544-1551 (IF = 7.307, Top journal)[2] Lei Du, Heng Huang, Jingwen Yan, Sungeun Kim, Shannon L. Risacher, Mark Inlow, Jason H. Moore, Andrew J. Saykin, Li Shen*. Structured sparse CCA for brain imaging genetics via graph OSCAR. BMC Systems Biology: 2016,10(3) ,335-345 (IF = 2.303)[3] Lei Du, Tuo Zhang, Kefei Liu, Xiaohui Yao, Jingwen Yan, Shannon L. Risacher, Lei Guo, Andrew J. Saykin, Li Shen*. Sparse Canonical Correlation Analysis via truncated -norm with application to brain imaging genetics. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Shenzhen, China, Dec. 14-18, 2016, pp: 707-711[4] Xiao Li#, Lei Du#, Tuo Zhang#, Xintao Hu, Xi Jiang, Lei Guo, Tianming Liu*. Species Preserved and Exclusive Structural Connections Revealed by Sparse CCA. The 19th International Conference Medical Image Computing and Computer-Assisted Intervention (MICCAI), Athens, Greece, October 17-21, 2016, Proceedings, Part I: 2016, pp: 123-131 (# equal contribution, 医学图像领域顶级会议)[5] Jingwen Yan, Lei Du, S. L. Risacher, Li Shen, A. J. Saykin. Identification of diagnosis related imaging genomics associations through outcome-guided sparse CCA: An Alzheimer’s disease study. The 12th International Conference Imaging Genetics Conference (IIGC), Irvine, CA, Jan 18-19, 2016.2015:[1] Lei Du*, Qinbao Song, Lei Zhu, Xiaoyan Zhu. A Selective Detector Ensemble for Concept Drift Detection. The Computer Journal: 2015 ,58(3) ,457—471 (IF = 1.00)[2] Lei Du, Jingwen Yan, Sungeun Kim, Shannon L. Risacher, Heng Huang, Mark Inlow, Jason H. Moore, Andrew J. Saykin, Li Shen. GN-SCCA: GraphNet Based Sparse Canonical Correlation Analysis for Brain Imaging Genetics. The 8th International Conference on Brain Informatics and Health (BIH): 2015, pp: 275-284[3] Du, Lei* and Chakraborty, A* and Chiang CW and Cheng, L and Quinney SK and Wu HY and Zhang P and Li Lang, and Shen Li. Graphic mining of high-order drug interactions and their directional effects on myopathy using electronic medical records. CPT: Pharmacometrics & Systems Pharmacology, 2015, 4(8):481-488. DOI: 10.1002/psp4.59. (* equal contribution)[4] Zhang P* and Du, Lei*  and Wang L and Liu M and Cheng L and Chiang CW and Wu HY and Quinney SK and Shen, Li and Li Lang. A mixture dose-response model for identifying high-dimensional drug interaction effects on myopathy using electronic medical record databases. CPT: Pharmacometrics & Systems Pharmacology, 2015, 4(8):474-480. DOI: 10.1002/psp4.53. (* equal contribution)[5] Yan Jingwen and Du, Lei and Kim, S and Risacher, SL and Huang, H and Inlow, M and Moore, JH and Saykin, AJ and Shen, Li, for the ADNI. (2015) BoSCCA: Mining stable imaging and genetic associations with implicit structure learning. MICCAI Workshop on Imaging Genetics (MICGen), October 9, 2015.2014:[1] Lei Du*, Qinbao Song, Xiaolin Jia. Detecting concept drift: An information entropy based method using an adaptive sliding window. Intelligent data analysis: 2014 ,18(3) ,337--364 (IF = 0.631)[2] Lei Du, Jingwen Yan, Sungeun Kim, Shannon L. Risacher, Heng Huang, Mark Inlow, Jason H. Moore, Andrew J. Saykin, Li Shen*. A Novel Structure-aware Sparse Learning Algorithm for Brain Imaging Genetics. The 17th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), Boston, USA, Sep. 14-18, 2014, pp: 329-336 (Co-first author, 医学图像领域顶级会议)[3] Jingwen Yan, Lei Du, Sungeun Kim, Shannon L. Risacher, Heng Huang, Jason H. Moore, Andrew J. Saykin, Li Shen. Transcriptome-guided amyloid imaging genetic analysis via a novel structured sparse learning algorithm. Bioinformatics: 2014 ,30(17) ,i564--i571[4] Yan, Jingwen and Zhang, Hui and Du, Lei and Wernert, E and Saykin, AJ and Shen, Li (2014) Accelerating sparse canonical correlation analysis for large brain imaging genetics data. The Annual Extreme Science and Engineering Discovery Environment Conference (XSEDE). Atlanta, GA, July 13-18, 2014. doi 10.1145/2616498.2616515.[5] Yao, Xiaohui and Chen, Rui and Kim, S and Yan J and Du, Lei and Nho, K and Foroud, TM and Moore, JH and Weiner, MW and Saykin, AJ and Shen, Li. Genetic Findings using ADNI Multimodal Quantitative Phenotypes: A Review of Papers Published in 2013. Alzheimer's Association International Conference on Alzheimer's Disease (AAIC), Copenhagen, Denmark, July 12-17, 2014.[6] Zhu, Lei and Song, Qinbao and Guo, Yuchen and Du, Lei and Zhu, Xiaoyan and Wang, Guangtao. A Coding Method for Efficient Subgraph Querying on Vertex- and Edge-Labeled Graphs. PLOS ONE: 2014 ,9(5)2013:[1] 杜磊, 杜星, 宋擒豹. 一种k-NN分类器k值自动选取方法. 控制与决策: 2013 ,28(7) ,1073. (中国科技期刊卓越行动计划梯队期刊)[2] Lei Du, Qinbao Song. A Simple Classifier Based on a Single Attribute. The 14th IEEE International Conferences on High Performance Computing and Communications (HPCC). Liverpool, UK, Jun. 24-28, 2012, pp: 660-665Book Chapter:[1] Yan, Jingwen# and Du, Lei# and Yao, Xiaohui# and Shen, Li. Book Chapter in Machine Learning and Medical Imaging: Machine learning in brain imaging genomics. Elsevier: 2016. (# equal contribution)