蔡立军
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蔡立军,男,中共党员,计算机应用技术专业博士,教授,博士生导师。1982年考入华中工学院(现华中科技大学),先后获华中工学院工学学士学位、湖南大学的工程硕士学位、工学博士学位。先后任湖南大学远程与继续教育学院副院长、湖南大学教务处副处长,国家超级计算长沙中心湖南大学建设办公室主任。现任湖南大学现代工程训练中心主任兼教务处副处长,教育部工程训练教学指导委员会委员;中南地区港澳特区金工研究会副理事长;湖南省物联网协会副理事长。
近年来,主持国家科技支撑计划项目1项,国家自然科学基金项目2项,湖南省自然科学基金重点项目1项,长沙市科技重大专项项目3项,参与国家发改委重大项目2项。发表SCI论文40多篇。获湖南省科技进步奖二等奖1项、三等奖2项。先后承担教育部第一批、第二批新工科研究与实践项目各1项;承担首批及第二批国家级一流本科课程2门、省级一流本科课程2门;2023年,获国家级教学成果二等奖2项,2016年、2019年、2022年连续三次获得湖南省教学成果奖一等奖,并获得二等奖2项。培养博士、硕士研究生80多人。
中文名: 蔡立军 英文名:
学历: 博士 职称: 教授
联系电话: 0731-88821513 电子邮件: ljcai@hnu.edu.cn
研究方向: 机器学习、生物信息学、云计算、大数据
联系地址: 湖南省长沙市岳麓区麓山南路2号,湖南大学信息科学与工程学院(410082)
所属机构:  软件工程系  学院教师
代表性科研项目:

1、国家自然科学基金面上项目,62472165, 基于知识增强和多模态数据驱动的分子性质预测方法研究,2025/01 - 2028/1250万元,参与(排名2)

2、杭州海康威视数字技术股份有限公司委托项目,多模态大模型和大语言模型研究及应用(编号:H202491420100),

经费:226万,主持

3、甲型流感病毒基因组信息分析及应用算法研究(国家自然科学基金,编号:61272395),

经费:80万,主持

4、复杂疾病的基因调控网络构建及调控机制研究(国家自然科学基金,编号:61472127),

经费:83万,主持

5、基于超级计算和云计算技术的资源中心关键技术开发与典型应用示范——基于超级计算的工业设计资源中心技术

开发与集成技术平台(国家科技支撑计划项目,编号:2012BAH09B00),经费:296万,首席科学家

6、基于超算技术的关键技术研究与开发应用--基于超级计算机的云平台研发与产业化示范应用(长沙市科技重大专项项目,

编号:K1106004-11-1,K1204006-11-1, K1306004-11-1),经费:150万,首席科学家

7、省自然科学基金重点项目,湘基金委字(2012)4 号,肿瘤基金表达谱数据分析方法研究,2012/10-2014/12,

10万,主持


学术论文

[1] Yi Sun; Lijun Cai; Bo Liao; Wen Zhu; Junlin Xu,A Robust Oversampling Approach for Class Imbalance Problem with Small Disjuncts.IEEE Transactions on Knowledge and Data Engineering, 2023, 35(6): 5550-5562(CCF A类)

[2] Y. Sun, L. Cai, B. Liao and W. Zhu,"Minority Sub-region Estimation-based Oversampling for ImbalanceLearning," in IEEE Transactions on Knowledge and Data Engineering, doi: 10.1109/TKDE.2020.3010013.(CCF A)

[3] Lijun Cai, Li Wang, Xiangzheng Fu, Chenxing Xia, Xiangxiang Zeng, Quan Zou,ITP-Pred: an interpretable method for predicting, therapeutic peptides withfused features low-dimension representation. Briefings in Bioinformatics, 2020,https://doi.org/10.1093/bib/bbaa367. (中科院一区,IF 20189.101) ESI高被引论文

[4] Xiangzheng Fu, LijunCai, Xiangxiang Zeng, Quan Zou, StackCPPred: a stacking and pairwise energycontent-based prediction of cell-penetrating peptides and their uptakeefficiency, Bioinformatics, Volume 36, Issue 10, 15 May 2020,Pages 3028–3034, https://doi.org/10.1093/bioinformatics/btaa131(生物信息学顶级期刊,中科院小类一区,IF2019: 5.61) 

[5] Lijun Cai, Xuanbai Ren, Xiangzheng Fu, Li Peng, Mingyu Gao, Xiangxiang Zeng.iEnhancer-XG: interpretable sequence-based enhancers and their strengthpredictor,Bioinformatics, 2020, https://doi.org/10.1093/bioinformatics/btaa914(生物信息学顶级期刊,中科院小类一区,IF2019: 5.61) ESI高被引论文

[6] Junlin Xu, Lijun Cai, Bo Liao, Wen Zhu,JiaLiang Yang. CMF-Impute: an accurate imputation tool for single-cell RNA-seqdata. Bioinformatics, Volume 36, Issue 22-23, 1 December 2020, Pages 55635564, https://doi.org/10.1093/bioinformatics/btaa664.(生物信息学顶级期刊,中科院小类一区,IF2019: 5.61) 

[7] Xianfang Tang, Lijun Cai, Yajie Meng, JunLinXu, Changcheng Lu and Jialiang Yang. Indicator Regularized Non-Negative MatrixFactorization Method-Based Drug Repurposing for COVID-19. Frontiers inImmunology, 2021. https://doi.org/10.3389/fimmu.2020.603615.(中科院二区顶刊,IF2019: 5.085) 

[8] Wei Xia, Wen Zhu, Bo Liao, Min Chen, Lijun Cai,Lei Huang,Novel architecture for long short-term memory used in questionclassification, Neurocomputing, Volume 299, 2018, https://doi.org/10.1016/j.neucom.2018.03.020.(中科院二区顶刊,IF2019: 4.438) 

[9] B. Liao, Y. Jiang, W. Liang, W. Zhu, L. Caiand Z. Cao, "Gene Selection Using Locality Sensitive LaplacianScore," in IEEE/ACM Transactions on Computational Biology andBioinformatics, vol. 11, no. 6, pp. 1146-1156, 1 Nov.-Dec. 2014, doi:10.1109/TCBB.2014.2328334. (CCF B) 

[10] Junlin Xu, Wen Zhu, Lijun Cai, Bo Liao,Yajie Meng, Ju Xiang, Dawei Yuan, Geng Tian, Jialiang Yang. "LRMCMDA:Predicting miRNA-Disease Association by Integrating Low-Rank Matrix CompletionWith miRNA and Disease Similarity Information," in IEEE Access, vol. 8,pp. 80728-80738, 2020, doi: 10.1109/ACCESS.2020.2990533. 

[11] T. Meng, L. Cai, T. He, L. Chen and Z. Deng,"Local Higher-Order Community Detection Based on Fuzzy MembershipFunctions," in IEEE Access, vol. 7, pp. 128510-128525, 2019, doi:10.1109/ACCESS.2019.2939535. 

[12] Weibiao Li, Bo Liao, Wen Zhu, Min Chen, Zejun Li,Xiaohui Wei, Lihong Peng, Guohua Huang, Lijun Cai & HaoWen Chen.Fisher Discrimination Regularized Robust Coding Based on a Local Center forTumor Classification. Scientific reports, 2018.    

[13] Bo Li, Lijun Cai, Bo Liao, XiangzhengFu,Pingping Bing and Jialiang Yang. Prediction of Protein SubcellularLocalization Based on Fusion of Multi-view Features. Molecules, 2019https://doi.org/10.3390/molecules24050919. 

[14] Changlong Gu, Bo Liao, Xiaoying Li, Lijun Cai,Zejun Li, Keqin Li , Jialiang Yang . Global network random walk for predictingpotential human lncRNA-disease associations. Sci Rep 7, 12442 (2017). https://doi.org/10.1038/s41598-017-12763-z. 

[15] Junlin Xu, Lijun Cai, Bo Liao, Wen Zhu, PengWang, Yajie Meng, Jidong Lang, Geng Tian and Jialiang Yang.IdentifyingPotential miRNAsDisease Associations WithProbability Matrix Factorization. Frontiers in Genetics, 2019. https://doi.org/10.3389/fgene.2019.01234. 

[16] Xiangzheng Fu, Wen Zhu, Lijun Cai, Bo Liao,Lihong Peng, Yifan Chen and Jialiang Yang, Improved Pre-miRNAs IdentificationThrough Mutual Information of Pre-miRNA Sequences and Structures. Frontiers inGenetics, 2019. https://doi.org/10.3389/fgene.2019.00119. 

[17] Peng Wang, Wen Zhu, Bo Liao, Lijun Cai,Lihong Peng and Jialiang Yang. Predicting Influenza Antigenicity by MatrixCompletion With Antigen and Antiserum Similarity. Frontiers in Genetics, 2018.https://doi.org/10.3389/fmicb.2018.02500. 

[18] Bo Liao, Qilin Xiang, Lijun Cai, Zhi Cao, Anew graphical coding of DNA sequence and its similarity calculation, Physica A:Statistical Mechanics and its Applications,Volume 392, Issue 19, 2013,Pages4663-4667,ISSN 0378-4371, https://doi.org/10.1016/j.physa.2013.05.015. 

[19] L. Chen, J. Zhang, L. Cai and Z. Deng,"Fast community detection based on distance dynamics," in Tsinghua Scienceand Technology, vol. 22, no. 6, pp. 564-585, December 2017, doi:10.23919/TST.2017.8195341. 

[20]  Zejun Li, BoLiao, Yun Lia, Wenhua Liu, Min Chen and Lijun Cai. Gene functionprediction based on combining gene ontology hierarchy with multi-instance multi-labellearning. ROYAL SOCIETY OF CHEMISTRY, 2018. DOI: 10.1039/C8RA05122D. 

[21] Xiangzheng Fu, Bo Liao, Wen Zhu and Lijun Cai.New 3D graphical representation for RNA structure analysis and its applicationin the pre-miRNA identification of plants. ROYAL SOCIETY OF CHEMISTRY, 2018.DOI: 10.1039/C8RA04138E. 

[22] Bo Liao, Sumei Ding, Haowen Chen, Zejun Li and LijunCai. Identifying human microRNAdisease associations by a new diffusion-basedmethod. Journal of Bioinformatics and Computational Biology, 2015. https://doi.org/10.1142/S0219720015500146. 

[23] Min Chen, Xingguo Lu, Bo Liao, Zejun Li, LijunCai, Changlong Gu. Uncover miRNA-Disease Association by Exploiting GlobalNetwork Similarity. PLOS ONE, 2016. https://doi.org/10.1371/journal.pone.0166509.  

[24] Bo Liao, Yan Jiang, Guanqun Yuan, Wen Zhu, LijunCai, Zhi Cao. Learning a Weighted Meta-Sample Based Parameter Free SparseRepresentation Classification for Microarray Data. PLOS ONE, August 12, 2014. https://doi.org/10.1371/journal.pone.0104314. 

[25] Lei Chen, Jing Zhang, Lijun Cai, Rui Li,Tingqin He, Tao MengMTAD: A Multitarget Heuristic Algorithm for Virtual Machine Placement,International Journal of Distributed Sensor Networks, 2015. https://doi.org/10.1155/2015/679170.