科研工作:

2016年3月至今  西北工业大学自动化学院 助理教授(讲师)；2013年8月至2016年1月 美国印第安纳大学医学院 博士后；2009年3月至2010年2月 中国科学院计算技术研究所 研究助理。科研项目： [1] 2017-2019 国家自然科学基金青年项目（No. 61602384，主持）[2] 2017-2018 陕西省自然科学基础研究计划青年项目 （No. 2017JQ6001，主持）[3] 2017-2018 2017年度留学人员科技活动项目择优资助 (主持)[4] 2017-2018 中国博士后科学基金面上项目（No.2017M613202，主持）[5] 2017-2018 陕西省博士后科研资助项目 (主持)[6] 2016-2017 中央高校基本科研业务费（启动）（主持） 2017:[1]  Lei Du, Kefei Liu, Xiaohui Yao, JingwenYan, Shannon L. Risacher, Junwei Han, Lei Guo, Andrew J. Saykin, Li Shen.Pattern Discovery in Brain Imaging Genetics via SCCA Modeling with a GenericNon-convex Penalty. Scientific Reports: 2017.10, accepted. (IF = 4.2589)[2]  Lei Du, Kefei Liu, Tuo Zhang, XiaohuiYao, Jingwen Yan, Shannon L. Risacher, Junwei Han, Lei Guo, Andrew J. Saykin, LiShen. A Novel SCCA Approach via Truncated L1-norm and Truncated Group Lasso forBrain Imaging Genetics. Bioinformatics: 2017.9, accepted.(IF = 7.307, top journal)[3]  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 andGenetic Factors via A Novel Structured SCCA Approach. IPMI’17: 25th BiennialInternational Conference on Information Processing in Medical Imaging,Boone, USA, June 24-30, 2017 (EI, a preeminent biennial internationalconference)[4]  Yuming Huang, Lei Du, Kefei Liu, Xiaohui Yao,Shannon L. Risacher, Lei Guo, Andrew J. Saykin, Li Shen. A fast SCCA algorithmfor big data analysis in brain imaging genetics. MICGen 2017: MICCAI Workshop onImaging Genetics, 9 pages, September 10, 2017. (Corresponding author)[5]  Xiao Li, Tuo Zhang, QinglinDong, Shu Zhang, Xintao Hu, Lei Du,Lei Guo, Tianming Liu. Predicting cortical 3-hinge locations via structuralconnective features. 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 ImagingGenetics: An Improved GraphNet Method. Bioinformatics: 2016,32(10),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. BMCSystems 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, LiShen. Sparse Canonical Correlation Analysis via truncated -norm withapplication to brain imaging genetics. BIBM’16: IEEE International Conference onBioinformatics and Biomedicine, Shenzhen, China, Dec. 14-18, 2016, pp:707-711[4]  Xiao Li*, Lei Du*, Tuo Zhang*, Xintao Hu, Xi Jiang, Lei Guo, TianmingLiu. Species Preserved and Exclusive Structural Connections Revealed by SparseCCA. MICCAI’16: 19th International Conference Medical Image Computing andComputer-Assisted Intervention, Athens, Greece, October 17-21, 2016,Proceedings, Part I: 2016, pp: 123-131 (* equal contribution)[5]  Yan, Jingwen and Du, Lei and Risacher, SL andShen Li and Saykin AJ, and for the ADNI. (2016) Identification of diagnosisrelated imaging genomics associations through outcome-guided sparse CCA: AnAlzheimer’s disease study. IIGC’16: 12th International Imaging GeneticsConference, Irvine, CA, Jan 18-19, 2016.2015:[1]  Lei Du, Qinbao Song, Lei Zhu,Xiaoyan Zhu. A Selective Detector Ensemble for Concept Drift Detection. TheComputer 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 forBrain Imaging Genetics. Brain Informatics and Health: 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 theirdirectional 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 ChiangCW and Wu HY and Quinney SK and Shen, Li and Li Lang. A mixture dose-responsemodel for identifying high-dimensional drug interaction effects on myopathyusing electronic medical record databases. CPT: Pharmacometrics & SystemsPharmacology, 2015, 4(8):474-480. DOI: 10.1002/psp4.53. (* equalcontribution)[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 theADNI. (2015) BoSCCA: Mining stable imaging and genetic associations withimplicit structure learning. MICGen 2015: MICCAI Workshop on ImagingGenetics, October 9, 2015.2014:[1]  Lei Du, Qinbao Song, Xiaolin Jia.Detecting concept drift: An information entropy based method using an adaptivesliding 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 ImagingGenetics. MICCAI’14: 17th International Conference on Medical Image Computing andComputer-Assisted Intervention, Boston, USA, Sep. 14-18, 2014, pp:329-336 (Co-first author)[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 structuredsparse learning algorithm. Bioinformatics: 2014 ,30(17),i564--i571[4]  Yan, Jingwen and Zhang, Hui andDu, Lei and Wernert, E andSaykin, AJ and Shen, Li (2014) Accelerating sparse canonical correlationanalysis for large brain imaging genetics data. XSEDE’14: The Annual ExtremeScience and Engineering Discovery Environment Conference, Article No.4, Atlanta, GA, July 13-18, 2014. doi 10.1145/2616498.2616515.[5]  Yao, Xiaohui and Chen, Rui andKim, S and Yan J and Du, Leiand 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 ofPapers Published in 2013. AAIC'14: Alzheimer's Association Int. Conf.on Alzheimer's Disease, Copenhagen, Denmark, July 12-17, 2014.[6]  Zhu, Lei and Song, Qinbao andGuo, Yuchen and Du, Lei andZhu, Xiaoyan and Wang, Guangtao. A Coding Method for Efficient Subgraph Queryingon Vertex- and Edge-Labeled Graphs. PLOS ONE: 2014 ,9(5)2013:[1]  Lei Du, Xing Du, Qinbao Song. Anautomatic selection method of k in k-NNclassifier. Control and Decision: 2013 ,28(7) ,1073.[2]  Lei Du, Qinbao Song. A SimpleClassifier Based on a Single Attribute. HPCC’ 12: 14th IEEE InternationalConferences on High Performance Computing and Communications.Liverpool, UK, Jun. 24-28, 2012, pp: 660-665Book Chapter:[1]  Yan, Jingwen* and Du, Lei* and Yao, Xiaohui* andShen, Li. Book Chapter in Machine Learning and Medical Imaging:Machine learning in brain imaging genomics. Elsevier: 2016. (*equalcontribution)

教育背景:

2003年9月-2007年7月  西北工业大学自动化学院；2007年9月-2013年6月  西安交通大学电信学院。