余国先
教授，博士生导师，齐鲁青年****
Email:gxyu@sdu.edu.cn; guoxian85@gmail.com
个人简介
山东大学教授，博士生导师，齐鲁青年****。2013年毕业于华南理工大学计算机应用技术专业，获工学博士学位，2013年-2020年在西南大学计算机与信息科学学院工作，2014-2015年香港浸会大学计算机科学系博士后，2011年至2013年美国乔治梅森大学计算机科学系公派联合培养博士生，重庆市学术技术带头人后备人选(2018)。
中国计算机学会会员（人工智能与模式识别专委会委员、生物信息学专委会委员、大数据专委会通讯委员），中国人工智能学会会员（机器学习专委会委员,生物信息学与人工生命专委会委员），IEEE/ACM会员，中国生物工程学会会员。担任KDD, NeurIPS, IJCAI, AAAI, ICDM, SDM, WSDM, ECAI和BIBM等国际国内重要会议程序委员会委员（Senior/Program Committee, Area Chair），和TPAMI, TNNLS, TKDE, TCBB, Information Fusion, Pattern Recognition, Genome Biology, Bioinforamtics, BiB,自动化学报，计算机学报，中国科学-信息科学等多个国内外著名期刊审稿人。
主要从事机器学习，数据挖掘及其在生物医学数据分析中的应用研究，获得重庆市科技奖励（自然科学）三等奖（2019）（余国先，郭茂祖，王峻等）。在国内外主流会议和期刊(KDD, AAAI, IJCAI, TKDE, TNNLS, TCYB, Bioinformatics, BiB, TCBB,中国科学-信息科学,计算机学报等)发表论文100余篇。主持(完成)国家自然科学基金3项，重庆市自然科学基金2项。
讲授《机器学习》、《数据库系统原理》、《Matlab程序设计》等课程。
教育经历
2007年-2013年，华南理工大学，计算机应用技术，工学博士
2003年-2007年，西安理工大学，软件工程，工学学士
主持科研项目
2019-2022，面向可变剪接异构体功能预测的数据整合方法研究 国家自然科学基金（**）
2018-2018，基于多层次数据集成的跨物种蛋白质功能预测研究，国家自然科学基金（**）
2015-2017，面向蛋白质功能预测的多标记学习方法研究与应用，国家自然科学基金（**）
2018-2020，面向跨物种蛋白质功能预测的多源异构数据表示与集成模型研究，重庆市基础与前沿研究项目
2014-2017，多标记学习方法在蛋白质功能预测中的研究与应用，重庆市基础与前沿研究项目
2014-2016，高维数据上的半监督学习研究与应用，人力资源与社会保障部留学人员科技活动项目择优资助
主要论文（+指导的学生，*通讯作者）
[1]. Xianxue Yu+,Guoxian Yu*, Jun Wang, Carlotta Domeniconi. Co-clustering Ensembles based on Multiple Relevance Measures,IEEE Transactions on Knowledge and Data Engineering(CCF Rank A), 2020.
[2]. Guoxian Yu,Xia Chen+, Carlotta Domeniconi, Jun Wang*, Zhao Li, Zili Zhang, Xiangliang Zhang. CMAL: Cost-effective Multi-label Active Learning by Querying Subexamples,IEEE Transactions on Knowledge and Data Engineering(CCF Rank A), 2020.
[3]. Guoxian Yu, Jinzheng Tu+, Jun Wang*, Carlotta Domeniconi, Xiangliang Zhang. Active Multi-Label Crowd Consensus,IEEE Transactions on Neural Networks and Learning Systems(CCF Rank B), 2020.
[4]. Jun Wang, Xing Wang+,Guoxian Yu*, Carlotta Domeniconi, Zhiwen Yu, Zili Zhang. Discovering Multiple Co-Clusterings with Matrix Factorization,IEEE Transactions on Cybernetics(CCF Rank B), 2020.
[5]. Qiaoyu Tan+,Guoxian Yu*, Jun Wang, Carlotta Domeniconi, Xiangliang Zhang. Individuality and Commonality based Multi-View Multi-Label Learning,IEEE Transactions on Cybernetics(CCF Rank B), 2020.
[6]. Xuanwu Liu+,Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Guoqiang Xiao, Maozu Guo. Weakly-supervised Cross-modal Hashing,IEEE Transactions on Big Data(CCF Rank C), 2020.
[7]. Jun Wang, Ziying Yang+, Carlotta Domeniconi, Xiangliang Zhang,Guoxian Yu*. Cooperative driver pathway discovery via fusion of multi-relational data of genes, miRNAs, and pathways,Briefings in Bioinformatics(CCF Rank B), 2020.
[8]. Guoxian Yu, Yuehui Wang+, Jun Wang*, Carlotta Domeniconi, Maozu Guo, Xiangliang Zhang. Attributed Heterogeneous Network Fusion via Collaborative Matrix Tri-factorization,Information Fusion(CCF Rank B), 2020, 63: 153-165.
[9]. Keyao Wang+, Jun Wang, Carlotta Domeniconi, Xiangliang Zhang, Guoxian Yu*. Differentiating isoform functions with collaborative matrix factorization,Bioinformatics(CCF Rank B), 2020, 36(6): 1864–1871.
[10].Guoxian Yu, Keyao Wang+, Carlotta Domeniconi, Maozu Guo*, Jun Wang*. Isoform function prediction based on bi-random walks on a heterogeneous network,Bioinformatics(CCF Rank B), 2020, 36(1): 303-310.
[11].Guoxian Yu*, Yuan Jiang, Jun Wang, Hao Zhang, Haiwei Luo*. BMC3C: Binning Metagenomic Contigs using Codon usage, sequence Composition and read Coverage,Bioinformatics(CCF Rank B), 2018, 34(24): 4171-4179.
[12].Guangyuan Fu+, Jun Wang, Carlotta Domeniconi,Guoxian Yu*. Matrix factorization based data fusion for the prediction of lncRNA-disease associations,Bioinformatics(CCF Rank B), 2018, 34(9): 1529-1537.
[13].Guangyuan Fu+, Jun Wang, Bo Yang,Guoxian Yu*. NegGOA: Negative GO Annotations Selection using Ontology Structure,Bioinformatics(CCF Rank B), 2016, 32(19): 2996-3004.
[14].Yingwen Zhao+, Jun Wang, Maozu Guo, Xiangliang Zhang,Guoxian Yu*. Cross-Species Protein Function Prediction with Asynchronous-Random Walk,IEEE/ACM Transactions on Computational Biology and Bioinformatics(CCF Rank B), 2020.
[15].Guoxian Yu, Keyao Wang+, Guangyuan Fu, Maozu Guo, Jun Wang*. NMFGO: Gene function prediction via nonnegative matrix factorization with Gene Ontology,IEEE/ACM Transactions on Computational Biology and Bioinformatics(CCF Rank B), 2020, 36(1): 303-310.
[16].Guoxian Yu*, Guangyuan Fu+, Jun Wang, Yingwen Zhao. NewGOA: predicting new GO annotations of proteins by bi-random walks on a hybrid graph,IEEE/ACM Transactions on Computational Biology and Bioinformatics(CCF Rank B), 2018, 15(4): 1390-1402.
[17].Guoxian Yu*, Guangyuan Fu+, Jun Wang, Hailong Zhu. Predicting Protein Function via Semantic Integration of Multiple Networks,IEEE/ACM Transactions on Computational Biology and Bioinformatics(CCF Rank B), 2016, 13(2): 220-232.
[18].Guoxian Yu*, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zili Zhang. Predicting Protein Function using Multiple Kernels,IEEE/ACM Transactions on Computational Biology and Bioinformatics(CCF Rank B), 2015, 12(1): 219-233.
[19].Guoxian Yu*, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zhiwen Yu. Protein Function Prediction with Incomplete Annotations,IEEE/ACM Transactions on Computational Biology and Bioinformatics(CCF Rank B), 2014, 11(3): 579-591.
[20].Guoxian Yu*, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zhiwen Yu. Protein Function Prediction using Multi-label Ensemble Classification,IEEE/ACM Transactions on Computational Biology and Bioinformatics(CCF Rank B), 2013, 10(4): 1045-1057.
[21].Jinzheng Tu+,Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Guoqiang Xiao, Maozu Guo. Multi-Label Crowd Consensus via Joint Matrix Factorization,Knowledge and Information Systems(CCF Rank B), 2020, 36(1): 303-310.
[22].Guoxian Yu*, Guoji Zhang, Zili Zhang, Zhiwen Yu, Lin Deng. Semi-Supervised Classification based on Subspace Sparse Representation,Knowledge and Information Systems(CCF Rank B), 2015, 43 (1): 81-101.
[23].Guoxian Yu*, Guoji Zhang, Carlotta Domeniconi, Zhiwen Yu and Jane You. Semi-Supervised Classification based on Random Subspace Dimensionality Reduction,Pattern Recognition(CCF Rank B), 2012, 45(3): 1119-1135.
[24].Yingwen Zhao+, Jun Wang, Jian Chen, Xiangliang Zhang, Maozu Guo*,Guoxian Yu*. A Literature Review of Gene Function Prediction by Modeling Gene Ontology,Frontier in Genetics, 2020, 11: 400.
[25].Yuehui Wang+, Maozu Guo, Yazhou Ren, Lianyin Jia,Guoxian Yu*. Drug Repositioning based on Individual Bi-random Walks on a Heterogeneous Network,BMC Bioinformatics(CCF Rank C), 2019, 20(S15): 547.
[26].Guoxian Yu*, Chang Lu+, Jun Wang. NoGOA: predicting noisy GO annotations using evidences and sparse representation,BMC Bioinformatics(CCF Rank C), 2017, 18: 350.
[27].Guoxian Yu*, Hailong Zhu, Carlotta Domeniconi. Predicting Protein Function using Incomplete Hierarchical Labels,BMC Bioinformatics(CCF Rank C), 2015, 16: 1.
[28].Guoxian Yu*, Hailong Zhu, Carlotta Domeniconi, Jiming Liu. Predicting protein function via downward random walks on a gene ontology,BMC Bioinformatics(CCF Rank C), 2015, 16: 271.
[29].Guoxian Yu*, Wei Luo, Guangyuan Fu, Jun Wang. Interspecies gene function prediction using semantic similarity,BMC Systems Biology, 2016, 10: 361.
[30].Guoxian Yu*, Hailong Zhu, Carlotta Domeniconi, Maozu Guo. Integrating Multiple Networks for Protein Function Prediction,BMC Systems Biology, 2015, 9(S1): S3.
[31].Guoxian Yu*, Guangyuan Fu+, Chang Lu+, Yazhou Ren, Jun Wang*. BRWLDA: Bi-random walks for predicting lncRNA-disease associations,Oncotarget, 2017, 8(36): 60429-60446.
[32].Xia Chen+,Guoxian Yu*, Qiaoyu Tan, Jun Wang. Weighted Samples based Semi-Supervised Classification,Applied Soft Computing, 2019, 79: 46-58.
[33].Jun Wang, Guangjun Yao,Guoxian Yu*. Semi-supervised classification by discriminative regularization,Applied Soft Computing, 2017, 58: 245-255.
[34].Guoxian Yu, Guoji Zhang, Zhiwen Yu*, Carlotta Domeniconi, Jane You, Guoqiang Han. Semi-Supervised Ensemble Classification in Subspaces, Applied Soft Computing,Applied Soft Computing,2012, 12(5): 1511-1522.
[35].Yuehui Wang+,Guoxian Yu*, Jun Wang, Guangyuan Fu, Maozu Guo, Carlotta Domeniconi. Weighted Matrix Factorization on multi-relational data for LncRNA-Disease Association prediction,Methods, 2020, 173: 32-43.
[36].Yingwen Zhao+, Guangyuan Fu+, Jun Wang, Maozu Guo,Guoxian Yu*. Gene function prediction based on Gene Ontology Hierarchy Preserving Hashing,Genomics, 2019, 111(3): 334-342.
[37].Qiaoyu Tan+, Yezi Liu, Xia Chen,Guoxian Yu*. Multi-Label Classification based on Low Rank Representation for Image Annotation,Remote Sensing, 2017, 9(2): 109.
[38].赵颖闻+，王峻，郭茂祖，张自力，余国先*.基于0-1矩阵分解的蛋白质功能预测,中国科学-信息科学, 2019, 49(9): 1159-1174.
[39].路畅+,陈霞，王峻，余国先*，余志文.基于稀疏语义的蛋白质噪声功能标注识别,中国科学－信息科学, 2018. 48(8): 1035-1050.
[40].余国先*，傅广垣+，王峻，郭茂祖.基于降维的蛋白质不相关功能预测,中国科学－信息科学, 2017, 47(10): 1349-1368.
[41].傅广垣+，余国先*，王峻，张自力.基于有向混合图的蛋白质新功能预测,中国科学-信息科学,2016, 46(4): 461-475.
[42].王星+，王峻*，余国先，郭茂祖.基于网络约束双聚类的癌症亚型分类,计算机学报, 2019, 42(6): 1274-1288.
[43].谭桥宇+，余国先，王峻*，郭茂祖.基于标记与特征依赖最大化的弱标记集成分类,软件学报, 2017, 28(11): 2851-2864.
[44].余国先，王可尧，傅广垣，王峻*，曾安.基于多网络数据协同矩阵分解的蛋白质功能预测,计算机研究与发展, 2017, 54(12): 2660-2673.
[45].傅广垣+，余国先*，王峻，郭茂祖.基于正负样例的蛋白质功能预测,计算机研究与发展, 2016, 53(8): 1753-1765.
主要会议论文
[46].Guangyang Han+, Jinzheng Tu+,Guoxian Yu*, Jun Wang, Carlotta Domeniconi. Crowdsourcing with Multiple-Source Knowledge Transfer, 29th International Joint Conference on Artificial Intelligence (IJCAI) (CCF Rank A), 2020, pp. 2908-2914.
[47].Yuying Xing+,Guoxian Yu*, Jun Wang, Carlotta Domeniconi, Xiangliang Zhang. Weakly-Supervised Multi-view Multi-instance Multi-label Learning, 29th International Joint Conference on Artificial Intelligence (IJCAI) (CCF Rank A), 2020, pp. 2908-2914.
[48].Shichao Pei, Lu Yu,Guoxian Yu, Xiangliang Zhang. REA: Robust Cross-lingual Entity Alignment Between Knowledge Graphs, 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) (CCF Rank A), 2020.
[49].Tingting Yu+,Guoxian Yu*, Jun Wang and Maozu Guo. Partial Multi-label Learning with Label and Feature Collaboration, 25th International Conference on Database Systems for Advanced Applications (DASFAA) (CCF Rank B), 2020.
[50].Shaowei Wei⁺, Jun Wang^*,Guoxian Yu, Carlotta Domeniconi, Xiangliang Zhang. Multi-View Multiple Clusterings using Deep Matrix Factorization, 34rd AAAI Conference on Artificial Intelligence (AAAI) (CCF Rank A), 2020, pp. 6348-6355.
[51].Jinzheng Tu⁺,Guoxian Yu*, Jun Wang, Carlotta Domeniconi, Xiangliang Zhang. Attention-Aware Answers of the Crowd, 20th SIAM Conference on Data Mining (SDM) (CCF Rank B), 2020, pp. 451-459.
[52].Shixin Yao⁺,Guoxian Yu^*, Carlotta Domeniconi, Jun Wang, Xiangliang Zhang. Multi-View Multiple Clustering, 28th International Joint Conference on Artificial Intelligence (IJCAI) (CCF Rank A), 2019, pp. 4121-4127.
[53].Xia Chen⁺,Guoxian Yu^*, Jun Wang, Carlotta Domeniconi, Zhao Li, Xiangliang Zhang. ActiveHNE: Active Heterogeneous Network Embedding, 28th International Joint Conference on Artificial Intelligence (IJCAI) (CCF Rank A), 2019, pp. 2123-2129.
[54].Xing Wang⁺, Jun Wang*, Carlotta Domeniconix,Guoxian Yu, Guoqiang Xiao, Maozu Guo. Multiple Independent Subspace Clusterings, 33rd AAAI Conference on Artificial Intelligence (AAAI) (CCF Rank A), 2019, pp. 5353-5360.
[55].Yuying Xing⁺, Guoxian Yu^*, Carlotta Domeniconi, Jun Wang, Zili Zhang, Maozu Guo Multi-View Multi-Instance Multi-Label Learning based on Collaborative Matrix Factorization, 33rd AAAI Conference on Artificial Intelligence (AAAI) (CCF Rank A), 2019, pp. 5508-5515.
[56].Xuanwu Liu+,Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Yazhou Ren, Maozu Guo. Ranking-based Deep Cross-modal Hashing, 33rd AAAI Conference on Artificial Intelligence (AAAI) (CCF Rank A), 2019, pp. 4400-4407.
[57].Zhao Li*, Xia Chen+, Xuming Pan, Pengcheng Zou, Yuchen Li,Guoxian Yu. SHOAL: Large-scale Hierarchical Taxonomy via Graph-based Query Coalition in E-commerce, 45th International Conference on Very Large Data Bases (VLDB) (CCF Rank A), 2019, 12(12): 1858-1861.
[58].Xuanwu Liu, Zhao Li, Jun Wang, Guoxian Yu^*, Carlotta Domeniconi, Xiangliang Zhang. Cross-modal Zero-shot Hashing, IEEE International Conference on Data Mining (ICDM) (CCF Rank B), 2019, pp. 449-458.
[59].Shixin Yao+,Guoxian Yu, Xing Wang, Jun Wang^*, Carlotta Domeniconi, Maozu Guo Discovering Multiple Co-Clusterings in Subspaces, SIAM Conference on Data Mining (SDM) (CCF Rank B), 2019, pp. 423-431.
[60].Yuehui Wang+,Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Xiangliang Zhang, Maozu Guo. Selective Matrix Factorization for Multi-Relational Data Fusion, 24th International Conference on Database Systems for Advanced Applications (DASFAA) (CCF Rank B), 2019, pp. 313-329.
[61].Yuying Xing+,Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Zili Zhang. Multi-Label Co-Training, 27th International Joint Conference on Artificial Intelligence (IJCAI) (CCF Rank A), 2018, pp.2882-2888.
[62].Qiaoyu Tan+,Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Zili Zhang. Incomplete Multi-View Weak-Label Learning, 27th International Joint Conference on Artificial Intelligence (IJCAI) (CCF Rank A), 2018, pp.2703-2709.
[63].Jinzheng Tu+,Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Guoqiang Xiao, and Maozu Guo. Multi-Label Answer Aggregation based on Joint Matrix Factorization, International Conference on Data Mining (ICDM) (CCF Rank B), 2018, pp.517-526.
[64].Xing Wang+,Guoxian Yu, Carlotta Domeniconi, Jun Wang*, Zhiwen Yu, and Zili Zhang. Multiple Co-Clusterings, International Conference on Data Mining (ICDM) (CCF Rank B), 2018, pp. 1308-1313.
[65].Xia Chen+,Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Zhao Li, and Zili Zhang. Cost Effective Multi-label Active Learning via Querying Subexamples, International Conference on Data Mining (ICDM) (CCF Rank B), 2018, pp. 905-910.
[66].Guoxian Yu*, Xia Chen+, Carlotta Domeniconi, Jun Wang, Zhao Li, Zili Zhang, and Xindong Wu. Feature-induced Partial Multi-label Learning, International Conference on Data Mining (ICDM) (CCF Rank B), 2018, pp. 1398-1403.
[67].Qiaoyu Tan+,Guoxian Yu*, Jun Wang, Zili Zhang, Carlotta Domeniconi. Multi-view Weak-label Learning based on Matrix Completion, 18th SIAM Conference on Data Mining (SDM) (CCF Rank B), 2018, pp. 450-458.
[68].Jie Zeng+,Guoxian Yu*, Jun Wang, Maozu Guo, Xiangliang Zhang. DMIL-III: Isoform-Isoform Interaction Prediction using Deep Multi-Instance Learning method. IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (CCF Rank B), 2019, pp. 171-176.
[69].Guangjie Zhou+, Jun Wang, Xiangliang Zhang, andGuoxian Yu*. DeepGOA: Predicting Gene Ontology Annotations of Proteins via Graph Convolutional Network, IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (CCF Rank B), 2019, pp. 1836-1841.
[70].Guoxian Yu, Yuehui Wang, Jun Wang*, Guangyuan Fu, Maozu Guo, Carlotta Domeniconi. Weighted Matrix Factorization based Data Fusion for Predicting lncRNA-disease Associations. IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (CCF Rank B), 2018, pp. 572-577.
[71].Xia Chen+,Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Zili Zhang. Matrix Factorization for Identifying Noisy Labels of Multi-label Instances, 15th Pacific Rim International Conference on Artificial Intelligence (PRICAI) (CCF Rank C), 2018, pp. 508-517
[72].Yanming Yu+,Guoxian Yu*, Xia Chen+ and Yazhou Ren. Semi-supervised Multi-label Linear Discriminant Analysis, 24th International Conference on Neural Information Processing (ICONIP) (CCF Rank C), 2017, pp. 688-698.
[73].Guoxian Yu*, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zili Zhang. Protein Function Prediction by Integrating Multiple Kernels, 23rd International Joint Conference on Artificial Intelligence (IJCAI) (CCF Rank A), 2013, pp.1869-1875.
[74].Guoxian Yu*, Carlotta Domeniconi, Huzefa Rangwala, Guoji Zhang. Protein Function Prediction using Dependence Maximization, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD) (CCF Rank B), 2013, pp. 574-589.
[75].Guoxian Yu*, Carlotta Domeniconi, Huzefa Rangwala, Guoji Zhang, Zhiwen Yu. Transductive Multi-label Ensemble Classification for Protein Function Prediction, Proceedings of the 18th ACM SIGKDD Conference on Knowledge Discovery in Database (KDD) (CCF Rank A), 2012, pp. 1077-1085.

招生意向
每年招收博士生1-2名，硕士生2-3人，本科生科研助理2-3人。
欢迎对机器学习、数据挖掘、生物医学数据分析、大数据挖掘和深度学习等研究方向和平台感兴趣的研究生（+本科生）加入研究小组。为同学们提供发表高水平科研与应用成果的精细指导，优良平台和学术氛围；为同学们提供争取创新项目、参加国内外科技竞赛、前往全球著名高校/企业深造与就业的机会与桥梁。
本人研究生从事的工作领域
任职于互联网公司（阿里巴巴，Vivo和美图等），银行，事业单位及大学。