余国先

发布时间:2016-04-28 来源:本站原创 作者:本站编辑   浏览次数:



姓名:余国先性别:
学历:博士 职称:副教授
部门:电子商务系电话:023-68254396
邮件地址:gxyu@swu.edu.cn; guoxian85@gmail.com

研究方向:机器学习,数据挖掘,生物信息学。





个人简介
工学博士,西南大学计算机与信息科学学院副教授,研究生导师,IEEE数据挖掘与大数据分析技术委员会委员,CCF会员(人工智能与模式识别专业委员会委员、生物信息学专业组委员、大数据专委会通讯委员),中国人工智能学会会员(生物信息学与人工生命专委会委员、机器学习专委会通讯委员),中国生物工程学会会员,ACM会员,西南大学机器学习与数据分析实验室主要负责人(团队主页http://mlda.swu.edu.cn/,个人相关主页:Google Scholar, DBLP

 

教育背景

2013-至今 西南大学计算机与信息科学学院从事教学科研工作

2014-2015年 香港浸会大学 计算机科学系 博士后研究员

2011-2013年 美国乔治梅森大学(George Mason University) 国家公派联合培养博士生

2007-2013年 华南理工大学 计算机科学与工程学院 计算机应用技术工学博士

2003-2007年 西安理工大学 计算机科学与工程学院 软件工程学士

 


研究兴趣:机器学习,数据挖掘与生物信息学,包括但不限于半监督学习,多标记学习,多视图学习,多示例学习,多核学习,集成学习,多源数据整合,大数据分析,深度学习与大规模并行数据分析,基于机器学习和数据挖掘技术的蛋白质功能预测、宏基因组分析、疾病关联分析等。

 

近年来,在国际顶级会议(SIGKDD, IJCAI, ECML/PKDD, SDM, ICDM等), 国内外知名期刊(Bioinformatics, IEEE/ACM Trans. on Computational Biology and Bioinformatics, BMC Bioinformatics, BMC Systems Biology, Knowledge and Information Systems, Pattern Recognition, Neurocomputing,中国科学-信息科学,软件学报,计算机研究与发展等)发表论文60余篇。

 

作为负责人主持(完成)国家自然科学基金青年基金,应急管理项目、重庆市自然科学基金项目、教育部中央高校重点项目和博士启动项目各1项。受邀担任KDD16, ICDM14-18, SDM14-18, CIDM14-16, CCFAI17, CCFBigData15-17, CBC16-17等国际国内会议程序委员会委员(Program Committee), IEEE/ACM Trans. on Computational Biology and Bioinformatics, Information Fusion, Neurocomputing,自动化学报和中国科学-信息科学等多个国内外著名期刊审稿人。

教学情况
本科生:数据库原理导论;Matlab程序设计与实践; Java程序设计
研究生: 机器学习;数据挖掘
西南大学含弘学院专业导师
论文情况

1.        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.

2.        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 C), In Print.

3.        Yingwen Zhao+, Guangyuan Fu+, Jun Wang, Maozu Guo, Guoxian Yu*. Gene function prediction based on Gene Ontology Hierarchy Preserving Hashing, Genomics, In Print.

4.        Long Zhang+, Guoxian Yu, Dawen Xia, Jun Wang*. Protein-Protein Interactions Prediction based on Ensemble Deep Neural Networks, Neurocomputing (CCF Rank C), In Print.

5.        Guoxian Yu*, Chang Lu+, Jun Wang. NoGOA: predicting noisy GO annotations using evidences and sparse representation, BMC Bioinformatics (CCF Rank C), 2017, 18: 350.

6.        Qiaoyu Tan+, Yanming Yu+, Guoxian Yu, Jun Wang*. Semi-supervised multi-label classification using incomplete label information, Neurocomputing (CCF Rank C), 2017, 260: 192-202.

7.        Jun Wang, Guangjun Yao, Guoxian Yu*. Semi-supervised classification by discriminative regularization, Applied Soft Computing, 2017, 58: 245-255.

8.        Jie Liu+, Guoxian Yu, Yuan Jiang+, Jun Wang*. HiSeeker: Detecting High-Order SNP Interactions Based on Pairwise SNP Combinations, Genes, 2017, 8(6): 153.

9.        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.

10.     Yanming Yu+, Jun Wang*, Qiaoyu Tan+, Lianyin Jia, Guoxian Yu. Semi-supervised Multi-label Dimensionality Reduction based on Dependence Maximization, IEEE ACCESS, 2017, 5: 21927-21940.

11.     Guoxian Yu, Yingwen Zhao+, Chang Lu+, Jun Wang*. HashGO: Hashing Gene Ontology for protein function prediction, Computational Biology and Chemistry, 2017, 71: 264-273.

12.     Jun Wang, Long Zhang, Lianyin Jia, Yazhou Ren, Guoxian Yu*. Protein-Protein Interactions Prediction using a Novel Local Conjoint Triad De of Amino Acids Sequence, International Journal of Molecular Sciences, 2017, 18(11), 2373.

13.     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.

14.     Yuan Jiang+, Jun Wang, Dawen Xia, Guoxian Yu*. EnSVMB: Metagenomics Fragments Classification using Ensemble SVM and BLAST, Scientific Reports, 2017, 7: 9440.

15.     Guoxian Yu, Xianxue Yu, Jun Wang*. Network-aided Bi-Clustering for discovering cancer subtypes, Scientific Reports, 2017, 7: 1046.

16.     Xianxue Yu+, Guoxian Yu, Jun Wang*. Clustering cancer gene expression data by projective clustering ensemble, PLoS ONE, 2017, 12(2): e0171429.

17.     Guangyuan Fu+, Jun Wang, Bo Yang, Guoxian Yu*. NegGOA: Negative GO Annotations Selection using Ontology Structure, Bioinformatics, 2016, 32(19): 2996-3004.

18.     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 (TCBB) (CCF Rank C), 2016, 13(2): 220-232.

19.     Guoxian Yu*, Wei Luo, Guangyuan Fu, Jun Wang. Interspecies gene function prediction using semantic similarity, BMC Systems Biology, 2016, 10: 361.

20.     Chang Lu+, Jun Wang, Zili Zhang, Pengyi Yang, Guoxian Yu*. NoisyGOA: Noisy GO annotations prediction using taxonomic and semantic similarity, Computational Biology and Chemistry, 2016, 65: 203-211.

21.     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.

22.     Guoxian Yu*, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zili Zhang. Predicting Protein Function using Multiple Kernels, IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) (CCF Rank C), 2015, 12(1): 219-233.

23.     Guoxian Yu*, Hailong Zhu, Carlotta Domeniconi. Predicting Protein Function using Incomplete Hierarchical Labels, BMC Bioinformatics (CCF Rank C), 2015, 16: 1.

24.     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.

25.     Guoxian Yu*, Hailong Zhu, Carlotta Domeniconi, Maozu Guo. Integrating Multiple Networks for Protein Function Prediction, BMC Systems Biology, 2015, 9(S1): S3.

26.     Guoxian Yu*, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zhiwen Yu. Protein Function Prediction with Incomplete Annotations, IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) (CCF Rank C), 2014, 11(3): 579-591.

27.     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 (TCBB) (CCF Rank C), 2013, 10(4): 1045-1057.

28.     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.

29.     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.

30.     Guoxian Yu*, Hong Peng, Jia Wei, Qianli Ma, Enhanced Locality Preserving Projections with Robust Path based Similarity, Neurocomputing (CCF Rank C), 2011, 74(4): 598-605.

 

国内期刊论文

31.     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, 2017. In Print.

32.     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.

33.     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.

34.     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.

35.     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.

36.     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.

 

会议论文

37.     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, In Print

38.     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, In Print

39.     Qiaoyu Tan+, Guoxian Yu*, Jun Wang, Zili Zhang, Carlotta Domeniconi. Multi-view Weak-label Learning based on Matrix Completion, SIAM Conference on Data Mining(SDM) (CCF Rank B), 2018.05

40.     Yuehui Wang+, Maozu Guo, Yazhou Ren, Lianyin Jia, Guoxian Yu*. Drug Repositioning based on Individual Bi-random Walks on a Heterogenous Network, 14th International Symposium on Bioinformatics Research and Applications (ISBRA), 2018, In Print

41.     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.

42.     Guoxian Yu*, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zili Zhang. Protein Function Prediction by Integrating Multiple Kernels, International Joint Conference on Artificial Intelligence (IJCAI) (CCF Rank A), 2013, 1869-1875.

43.     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, 8188 :574-589.

44.     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, 1077-1085.


指导学生获奖

[1]. 2017.12全国研究生数学建模二等奖(傅广垣,陈霞, 赵颖闻), 三等奖(杨子影, 刘玄武, 严扬洋)

[2]. 2017.09研究生国家奖学金(傅广垣,余显学,江源,陈霞), 西南大学一等奖学金(全体研究生)

[3]. 2017.05计算机与信息科学学院优秀导学团队(机器学习与数据分析实验室)

[4]. 2017.04中央高校基本业务科研费-学生项目(傅广垣,陈霞,刘捷)

[5]. 2016.11全国研究生数学建模一等奖(江源,陈霞, 张龙),二等奖(刘捷, 余显学, 姜琳)

[6]. 2016.10研究生国家奖学金(傅广垣, 路畅), 西南大学一等奖学金(全体研究生)

[7]. 2016.07重庆市研究生创新项目(傅广垣)

[8].  2016.05国家大学生创新创业训练计划项目(谭桥宇, 郁颜铭)

[9]. 2016.04西南大学计信院创新基金一等资助(路畅),二等资助(傅广垣)

[10]. 2016.04中央高校基本业务科研费-学生项目(路畅, 傅广垣)

[11]. 2015.11全国研究生数学建模三等奖2项(路畅,罗卫;江源,刘捷,王贵军)

[12]. 2015.08中国机器学习会议优秀学生论文奖(傅广垣)

[13]. 2014.11全国研究生数学建模三等奖1项(路畅,姚光军)



备注

欢迎对机器学习,数据挖掘,生物信息学,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)加入我们的研究队伍。我们为同学们提供发表高水平科研与应用成果的实验平台和良好宽松的学术氛围,为同学们提供争取各种国家和学校学院奖学金和创新项目、参加各种国内外相关竞赛奖项的机会,为同学们提供去往国内外知名高校(清华大学、哈尔滨工业大学、天津大学、香港中文大学、美国、澳洲和欧洲多所合作大学)深造的机会,去往国内知名IT企业和研究所(阿里、腾讯、百度等)实习交流的机会,欢迎喜欢科学研究与项目实践的同学加入我们的研究团队

欢迎访问我们团队主页: http://mlda.swu.edu.cn/ 了解更多团队情况。

 

邮件是联系我的最佳方式:gxyu@swu.edu.cn; guoxian85@gmail.com,我会尽快回复你的邮件。