李政伟，男，博士，副教授，博士生导师，同济大学博士后，通过软件设计师和系统分析师认证（全国前25名），入选江苏省高层次创新创业人才引进计划和中国矿业大学优秀青年骨干教师，加拿大访学期间与国际著名计算系统生物学专家Edwin Wang教授合作。

目前主要工作集中在利用深度学习、统计学习、推荐系统等技术在生物、医学领域以及工业计算机视觉领域进行探索和研究；主持国家自然科学基金面上项目2项，江苏省双创计划项目1项 ，江苏省博士后科研计划1项，中国矿业大学青年科研基金项目1项，作为骨干成员参与加拿大国家卫生研究院基金项目1项，国家自然科学基金重点项目2项，国家自然科学基金面上项目2项，主持和参与企业委托项目20余项；在IEEE-ACM Trans.、Bioinformatics、Molecular Therapy、Briefings in Bioinformatics、Scientific Reports、电子学报等国内外重要期刊和会议上发表学术论文80余篇，其中70余篇被SCI、EI检索，8篇影响因子大于10，单篇最高引用300余次，获得软件著作权10余项，出版专著1部。

现为中国生物信息学会（筹）生物医学数据挖掘与计算专委会委员，江苏省生物信息学会专委会委员，中国计算机学会会员，中国人工智能学会会员，中国工业与应用数学学会会员，担任IEEE/ACM Transactions on Computational Biology and Bioinformatics、PLoS Computational Biology、Bioinformatics、Briefings in Bioinformatics、Molecular Therapy、Neural Networks等国际期刊审稿专家。

先后讲授《高级语言程序设计》、《数据结构》、《机器学习》、《编译技术》、《数据库应用》、《Python Programming》（全英文）、《New Technology of Computer》（全英文）、《New Technology of Big Data》（全英文）、《生物信息学》（研究生）和《大数据分析与应用》（研究生）等课程。近年来出版教材3部，主持校级教改项目2项，参与省级和校级教改项目5项，指导大学生创新创业训练项目8项，先后荣获淮海科学技术二等奖、煤炭工业协会教育教学成果奖三等奖、中国矿业大学科技进步二等奖、优秀教学质量一等奖、百佳本科教学教师、优秀本科毕业设计指导教师、优秀班主任、模范班主任等荣誉。

欢迎对科研有浓厚兴趣、勤奋踏实、具有自主学习意识的同学报考，同时欢迎优秀本科生实习！

近期项目列表：

[1] 国家自然科学基金面上项目，基于多源异构数据融合的miRNA与疾病高精度关联预测研究，已结题，主持

[2] 江苏省高层次创新创业人才引进计划（双创博士），基于机器学习的miRNA与人类复杂疾病关联预测研究，已结题，主持

[3] 江苏省博士后科研资助计划，多视角 microRNA 与人类复杂疾病关联预测模型构建与分析，已结题，主持

[4] 企业委托项目, 矿山环形车场图像识别及控制技术研发,  在研，主持

[5] 加拿大国家卫生研究院基金项目，Predicting of breast cancer risk by integrating genomic, immunological and lifestyle factors，合作单位：加拿大卡尔加里大学附属foothills医院，已结题，骨干成员

[6] 国家自然科学基金重点项目，基因组非编码区变异与转录因子调控关系的计算分析方法研究，已结题，第2参与人

[7] 国家自然科学基金面上项目，多视角识别长非编码RNA和人类复杂疾病关联预测研究，已结题，第2参与人

[8] 国家自然科学基金面上项目，基于多源数据融合的药物响应和药物相关非编码RNA靶点预测研究，在研，第1参与人

近期论文列表： 

[1] Zheng-Wei Li（李政伟）, Li-Peng Wan, Lei Wang, Wen-Jing Wang, Ru Nie. HHOMR: A Hybrid High-order Moment Residual Model for MiRNA-Disease Association Prediction [J]. Briefings in Bioinformatics. 2024, 25(5): bbae412. (SCI，中科院一区，JCR 1区)

[2] Zheng-Wei Li（李政伟）, Xu Bai, Ru Nie, Yan-Yan Liu, Lei Zhang, Zhu-Hong You. Predicting miRNA-disease associations based on spectral graph transformer with dynamic attention and regularization [J]. IEEE Journal of Biomedical and Health Informatics. 2024.  10.1109/JBHI.2024.3438439. (SCI，中科院一区，JCR 1区)

[3] Wen-Jing Wang, Peng-Yong Han, Zheng-Wei Li（李政伟、通讯作者）, Ru Nie, Kang-Wei Wang, Lei Wang, Hong-Mei Liao. LMGATCDA: Graph Neural Network with Labeling Trick for Predicting CircRNA-Disease Associations [J]. IEEE-ACM Transactions on Computational Biology and Bioinformatics. 2024. 39(2): btad043.   (SCI, 中科院二区，JCR 1区) 

[4] Kang-Wei Wang, Zheng-Wei Li（李政伟，通讯作者）, Zhu-Hong You, Peng-Yong Han, Ru Nie. Adversarial dense graph convolutional networks for single-cell classification [J]. Bioinformatics, 2023, 39(2): btad043. (SCI，中科院二区，JCR 1区)

[5] Zheng-Wei Li（李政伟）, Qian-Kun Wang, Chang-An Yuan, Peng-Yong Han, Zhu-Hong You, Lei Wang. Predicting MiRNA-disease Associations by Graph Representation Learning Based on Jumping Knowledge Networks [J]. IEEE-ACM Transactions on Computational Biology and Bioinformatics, 2023, 20(5): 2629-2638. (SCI, 中科院二区，JCR 1区) 

[6] Huan Zhao, Zheng-Wei Li（李政伟、通讯作者）, Zhu-Hong You, Ru Nie, Tang-Bo Zhong. Predicting miRNA-disease Associations based on Neighbor Selection Graph Attention Networks [J]. IEEE-ACM Transactions on Computational Biology and Bioinformatics. 2023, 20(2):1298-1307. (SCI, 中科院二区，JCR 1区)  

[7] Tang-Bo Zhong, Zheng-Wei Li（李政伟、通讯作者）, Zhu-Hong You, Ru Nie, Huan Zhao. Predicting miRNA-disease associations based on graph random propagation network and attention network[J]. Briefings in Bioinformatics. 2022, 23(2): bbab589. (SCI, 中科院一区，JCR 1区) 

[8] Kai Zheng, Xin-Lu Zhang, Lei Wang, Zhu-Hong You, Bo-Ya Ji, Xiao Liang, Zheng-Wei Li（李政伟，通讯作者）. SPRDA: a link prediction approach based on the structural perturbation to inter disease-associated Piwi-Interacting RNAs [J]. Briefings in Bioinformatics, 2022, 24(1): bbac498. (SCI, 中科院一区，JCR 1区)

[9]  Zheng-Wei Li（李政伟）, Tang-Bo Zhong, De-Shuang Huang, Zhu-Hong You, Ru Nie. Hierarchical graph attention network for miRNA-disease association prediction [J]. Molecular Therapy, 2022, 30(4): 1775-1786. (SCI, 中科院一区，JCR 1区) 

[10] 李政伟, 李佳树, 尤著宏, 聂茹, 赵欢, 钟堂波. 基于异质图注意力网络的miRNA与疾病关联预测算法 [J]. 电子学报, 2022, 50(6): 1428-1435. (EI，中文高水平期刊， CCF A) 

[11] Jing Li, Chen Zhang, Zheng-Wei Li（李政伟，通讯作者）, Ru Nie, Peng-Yong Han, Wen-Jia Yang, Hong-Mei Liao. GCMCDTI: Graph convolutional autoencoder framework for predicting drug-target interactions based on matrix completion [J]. Journal of Bioinformatics and Computational Biology. 2022, 20(5): 2250023. (SCI) 

[12] Zheng-Wei Li（李政伟）, Jia-Shu Li, Ru Nie, Zhu-Hong You, Wen-Zheng Bao. GAEMDA: A Graph Auto-Encoder Model for MiRNA-Disease Associations Prediction [J]. Briefings in Bioinformatics, 2021, 22(4): bbaa240. (SCI, 中科院一区，JCR 1区)  

[13] Ru Nie, Zheng-Wei Li（李政伟、通讯作者）, Zhu-Hong You, Wen-Zheng Bao, Jia-Shu Li. Efficient framework for predicting miRNA-disease associations based on improved hybrid collaborative filtering [J]. BMC Medical Informatics and Decision Making, 2021, 21(S1): 254. (SCI)  

[14] Bai-Long Liu, Xiao-Yan Zhu, Lei Zhang, Zhi-Zheng Liang, Zheng-Wei Li(李政伟、通讯作者). Combined Embedding Model for MiRNA-Disease Association Prediction [J]. BMC Bioinformatics, 2021, 22, 161. (SCI, 中科院二区, JCR 2区)  

[15] Lei Zhang, Bai-Long Liu, Zheng-Wei Li（李政伟、通讯作者）, Xiao-Yan Zhu, Zhi-Zhen Liang, Ji-Yong An. Predicting MiRNA-disease associations by multiple meta-paths fusion graph embedding model [J]. BMC Bioinformatics, 2020, 21, 470 (SCI, 中科院二区, JCR 2区)  

[16] Jia-Shu Li, Zheng-Wei Li（李政伟、通讯作者）, Ru Nie, Zhu-Hong You, Wen-Zheng Bao. FCGCNMDA: Predicting MiRNA-Disease Associations by Apply-ing Fully Connected Graph Convolutional Networks [J]. Molecular Genetics and Genomics, 2020, 295(5):1197-1209 (SCI)  

[17] Zheng-Wei Li（李政伟）, Ru Nie, Zhu-Hong You, Chen Cao, Jia-Shu Li. Using Discriminative Vector Machine Model with 2DPCA to Predict Interactions among Proteins [J]. BMC Bioinformatics, 2019, 20 (S25): 694. (SCI，中科院二区, JCR 2区)  

[18] Zheng-Wei Li（李政伟）, Ru Nie, Zhu-HongYou, Yan Zhao, Xin Ge, Yang Wang. LRMDA: Using Logistic Regression and Random Walk with Restart for MiRNA-Disease Association Prediction [C]. Proceedings of the 15th International Conference on Intelligent Computing, Lecture Notes in Computer Sciences, 2019, 283-293 (EI, CCF C) 

[19] Zheng-Wei Li（李政伟）, Peng-Yong Han, Zhu-Hong You, Xiao Li, Yu-Sen Zhang, Hai-QuanYu, Ru Nie, Xing Chen. In silico prediction of drug-target interaction networks based on drug topological structure and protein sequences [J]. Scientific Reports. 2017, 9: 2045-2322 (SC , 中科院二区, JCR 2区) 

[20] Zheng-Wei Li（李政伟）, Zhu-Hong You, Xing Chen, De-Shuang Huang, Gui-Ying Yan, Ru Nie and Yu-An Huang. Accurate prediction of protein-protein interactions by integrating potential evolutionary information embedded in PSSM profile and discriminative vector machine classifier [J]. Oncotarget. 2017, 8(14): 23638-23649 (SCI, 中科院一区, JCR 1区 ) 

[21] Zheng-Wei Li（李政伟）, Zhu-Hong You, Xing Chen, Jie Gui and Ru Nie. Highly Accurate Prediction of Protein-Protein Interactions via Incorporating Evolutionary Information and Physicochemical Characteristics [J]. International Journal of Molecular Sciences. 2016, 17(9):1396-1407 (SCI, 中科院二区, JCR1区) 

[22] Ru Nie, Xiao-Bing Shen, Zheng-Wei Li（李政伟、通讯作者）, Yan-Xia Jiang, Hong-Mei Liao, Zhu-Hong You. Lightweight Coal Flow Foreign Object Detection Algorithm [C]. Proceedings of International Conference on Intelligent Computing 2024. (EI, CCF C) 

[23] Zheng-Tao Zhang, Peng-Yong Han, Zheng-Wei Li（李政伟、通讯作者）, Ru Nie, Qian-Qun Wang. Prediction of MiRNA-Disease Association based on Higher-Order Graph Convolutional Networks [C]. ICIC 2022. (EI, CCF C) 

[24] Feng Chang, Zhen-Qiong Chen, Cai-Xia Xu, Hai-Lei Liu, Peng-Yong Han, Zheng-Wei Li（李政伟、通讯作者）. Bioinformatic analysis of clear cell renal carcinoma via ATAC-seq and RNA-seq. Proceedings of the 18th International Conference on Intelligent Computing [C], Lecture Notes in Computer Sciences 2022. (EI, CCF C) 

[25] Lei Wang, Zheng-Wei Li（李政伟） , Jing Hu, Long Wong, Bo-Wei Zhao, Zhu-Hong You. A PiRNA-Disease Association Model Incorporating Sequence Multi-Source Information with Graph Convolutional Networks [J]. Applied Soft Computing. 2024, 157: 111523. (SCI, 中科院一区, JCR1区) 

[26] Lei Wang, Zheng-Wei Li（李政伟）, Zhu-Hong You, De-Shuang Huang, Leon Wong. GSLCDA: An Unsupervised Deep Graph Structure Learning Method for Predicting CircRNA-Disease Association [J]. IEEE Journal of Biomedical and Health Informatics. 2024, 28(3): 1742-1751. (SCI, 中科院一区, JCR1区) 

[27] Lei Wang; Zheng-Wei Li（李政伟）, Zhu-Hong You, De-Shuang Huang, Leon Wong. MAGCDA: A Multi-hop Attention Graph Neural Networks Method for CircRNA-disease Association Prediction [J]. IEEE Journal of Biomedical and Health Informatics. 2024, 28(3): 1752-1761.  (SCI, 中科院一区, JCR1区) 

[28] Meng-Meng Wei, Lei Wang, Yang Li, Zheng-Wei Li（李政伟）, Bo-Wei Zhao, Xiao-Rui Su, Yu Wei, Zhu-Hong You. BioKG-CMI: a multi-source feature fusion model based on biological knowledge graph for predicting circRNA-miRNA interactions [J]. SCIENCE CHINA Information Sciences. 2024, 67(8): 189104. (SCI, 中科院二区, JCR1区) 

[29] Xin-Fei Wang, Chang-Qing Yu, Zhu-Hong You, Yan Wang, Lan Huang, Yan Qiao, Lei Wang, Zheng-Wei Li. BEROLECMI: a novel prediction method to infer circRNA-miRNA interaction from the role definition of molecular attributes and biological networks [J]. BMC Bioinformatics. 2024, 25(1): 264. (SCI, 中科院三区, JCR1区) 

[30] Zhong-Hao Ren, Chang-Qing Yu, Li-Ping Li, Zhu-Hong You, Zheng-Wei Li（李政伟）, Shan-Wen Zhang, Xiang-Xiang Zeng, Yi-Fan Shang. SiSGC: A Drug Repositioning Prediction Model Based on Heterogeneous Simplifying Graph Convolution [J]. Journal of Chemical Information and Modeling. 2024, 64(1):238-249. (SCI, 中科院二区, JCR1区) 

[31] Xin-Fei Wang, Chang-Qing Yu, Zhu-Hong You, Yan Qiao, Zheng-Wei Li（李政伟）, Wen-Zhun Huang. An efficient circRNA-miRNA interaction prediction model by combining biological text mining and wavelet diffusion-based sparse network structure embedding [J]. Computers in Biology and Medicine. 2023, 165:107421. (SCI, 中科院二区, JCR1区) 

[32] Xin-Fei Wang, Chang-Qing Yu, Zhu-Hong You, Yan Qiao, Zheng-Wei Li（李政伟）, Wen-Zhun Huang, Ji-Ren Zhou, Hai-Yan Jin. KS-CMI: A circRNA-miRNA interaction prediction method based on the signed graph neural network and denoising autoencoder [J]. ISCIENCE. 2023, 26(8):107478. (SCI, 中科院二区, JCR1区) 

[33] Lei Wang, Leon Wong, Zheng-Wei Li（李政伟）, Yu-An Huang, Xiao-Rui Su, Bo-Wei Zhao, Zhu-Hong You. A machine learning framework based on multi-source feature fusion for circRNA-disease association prediction [J]. Briefings in Bioinformatics, 2022, 23(5): bbac388. (SCI, 中科院一区，JCR 1区) 

[34] Han-Yuan Zhang, Lei Wang, Zhu-Hong You, Lun Hu, Bo-Wei Zhao, Zheng-Wei Li（李政伟）, Yang-Ming Li. iGRLCDA: identifying circRNA-disease association based on graph representation learning [J]. Briefings in Bioinformatics. 2022. 23(3): bbac083. (中科院一区，JCR 1区) 

[35] Hao-Yuan Li, Zhu-Hong You, Lei Wang, Xin Yan, Zheng-Wei Li（李政伟）. DF-MDA: An effective diffusion-based computational model for predicting miRNA-disease association [J]. Molecular Therapy, 2021, 29(4):1501-1511. (SCI, 中科院一区, JCR 1区)  

[36] Kai Zheng, Zhu-Hong You, lei Wang, Yong Zhou, Li-Ping Li, Zheng-Wei Li（李政伟）. DBMDA: A Unified Embedding for Sequence-Based miRNA Similarity Measure with Applications to Predict and Validate miRNA-Disease Associations [J]. Molecular Therapy-Nucleic Acids, 2020,19: 602-611. (SCI, 中科院二区，JCR 1区) 

[37] Bo-Ya Ji, Zhu-Hong You, Yi Wang, Zheng-Wei Li（李政伟）, Leon Wong. DANE-MDA: Predicting microRNA-disease associations via deep attributed network embedding [J]. iScience, 2021, 24(6):102455. (SCI, 中科院二区，JCR 1区)   

[38] Jia Qu, Xing Chen, Jun Yin, Yan Zhao, Zheng-Wei Li（李政伟）. Prediction of potential miRNA-disease associations using matrix decomposition and label propagation [J]. Knowledge-Based Systems. 2019, 186. (SCI, 中科院一区，JCR 1区) 

[39] Zhu-Hong You, Zhi-An Huang, Ze-Xuan Zhu, Gui-Ying Yan, Zheng-Wei Li（李政伟）, Zhen-Kun Wen, Xing Chen. PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction [J]. PLOS computational biology. 2017, 13(3): 1553-7358. (SCI, 中科院二区, JCR 1区)

[40] Kai Zheng, Zhu-Hong You, Lei Wang, Yong Zhou, Li-Ping Li, Zheng-Wei Li（李政伟）. MLMDA: A Machine Learning Approach to Predict and Validate MicroRNA-Disease Associations by Integrating of Heterogenous Information Sources [J]. Journal of Translational Medicine. 2019,17(1): 260. (SCI, 中科院2二区，JCR 2区 )

指导研究生情况：

朱志鹏，2021级硕士研究生，毕业去向：京东。

刘树安，2021级硕士研究生，毕业去向：山东大学读博。

王康威，2021级硕士研究生。个人荣誉：荣获2023年度研究生国家奖学金，校级优秀学生荣誉称号。学术成果：发表SCI论文2篇。

李   晶，2020级硕士研究生。个人荣誉：荣获2023年度校级优秀硕士论文。学术成果：发表SCI论文1篇。

钟堂波，2020级硕士研究生。个人荣誉：荣获2022年度研究生国家奖学金，校级优秀学生荣誉称号。学术成果：发表学术论文4篇，其中以第一作者发表影响因子10分以上中科院一区SCI论文2篇。

李佳树，2019级硕士研究生。个人荣誉：荣获2021年度研究生校级一等奖学金，本科学校：南通大学；毕业去向：荣耀终端有限公司；学术成果：发表学术论文5篇，其中4篇SCI期刊论文（单篇最高影响因子13.994，中科院1区，JCR 1区），1篇高水平中文核心期刊（电子学报，CCF A类）。

深度学习

生物信息学

计算机视觉

模式识别