主要事迹(续前页): [3] Ling-Yun Dai, Chun-Mei Feng,   Jin-Xing Liu*, Chun-Hou Zheng*, Mi-Xiao Hou ,Jiguo Yu. Robust Nonnegative   Matrix Factorization via Joint Graph Laplacian and Discriminative Information   for Identifying Differentially Expressed Genes. Complexity. Vol.   2017, Article ID 4216797, 11 pages doi.10.1155/2017/4216797 (SCI一区, IF = 4.621) [4] Chun-Mei Feng, Jin-Xing   Liu*, Ying-Lian Gao, Juan Wang, Dong-Qin Wang, Yong Du. A graph-Laplacian PCA   based on L1/2-norm constraint for characteristic gene selection. IEEE   International Conference on Bioinformatics and Biomedicine. BIBM IEEE   Computer Society, 1795-1799. DOI: 10.1109/BIBM.2016.7822791 (CCF B级会议 EI检索) [5] Chun-Mei Feng, Ying-Lian   Gao, Jin-Xing Liu*, Chun-Hou Zheng, Sheng-Jun Li, Dong Wang. A Simple Review   of Sparse Principal Components Analysis. International Conference on   Intelligent Computing. ICIC 2016: 374-383. DOI:   10.1007/978-3-319-42294-7_33 (EI检索) [6] Ling-Yun Dai, Chun-Mei Feng,   Jin-Xing Liu*, Chun-Hou Zheng*, Mi-Xiao Hou ,Jiguo Yu. Robust Graph   Regularized Discriminative Nonnegative Matrix Factorization for   Characteristic Gene Selection IEEE International Conference on   Bioinformatics and Biomedicine. BIBM. IEEE Computer Society,   2016:1253-1258. (CCF B级会议EI检索) [7]Chun-Mei Feng,Jin-Xing Liu*,   Chun-Hou Zheng, Yong Xu*.Supervised Discriminative Sparse PCA for   Com-Characteristic Gene Selection and Tumor Classification on Multi-view   Biological Data. IEEE Transactions on Neural Networks and Learning   Systems二审(SCI 一区IF   = 6.108)  [8]Chun-Mei Feng,Jin-Xing Liu*, Xiang-Zhen Kong, Yong XuPCA via joint   graph Laplacian and sparse constraint: identify differentially expressed   genes and sample clustering on gene expression data. IEEE/ACM   Transactions on Computational Biology and Bioinformatics在审 [9]Chun-Mei Feng.Jin-Xing Liu*,   Xiang-Zhen Kong, Yong Xu*Dual Graph Regularization PCA: Closed Form Solution   for Bi-clustering to Find "Checkerboard" Structure on Gene   Expression Microarray Data. IEEE Transactions on Knowledge and Data   Engineering在审 参与项目详细如下: [1]国家级:面向癌症基因表达数据分析的稀疏建模方法研究;61702299;27万元;7/9 ; [2] 省级:动态安全数据外包关键问题研究;ZR2016FB24;7万元;5/5; [3] 厅级:基于稀疏表示理论的基因表达数据挖掘方法研究;J17LN15;3.5万元;7/9; [4]厅级:支持动态更新的安全数据外包;J16LN15;5.5万元;7/7; [5] 校级:基于稀疏约束的基因表达数据分析算法研究;xkj201621;0.5万元;5/7; 3)       学业成绩及获得奖学金、所受表彰奖励情况: [1] 2017年一等学业奖学金,排名1/25; [2] 2016年二等学业奖学金,排名14/25; [3]   201706  通过大学英语六级; [4] 20171116 校级优秀研究生荣誉称号; [5]WSB   2018  IAPR Student Travel Grant; [6]20171208 ‘党员之助’奖学金; [7] 20170601 校级优秀科技创新成果奖; [8] 20170713 校级研究生学位论文科研创新资助基金; [9] 20160601 校级第十届研究生学术论坛三等奖; 4)       参与校园文化及社会活动情况: [1]于深圳参加CCF B级国际学术会议BIBM 2016,并做英文口头报告;于兰州ICIC   2016国际会议中做poster; [2]获得Winter School on   Biometrics 2018生物特征识别冬令营资格、学生旅游资助金; [3] 201704被山东大学数学学院邀请做报告和交流学习访问; [4] 201705被浙江大学计算机学院CCNT实验室邀请做报告和交流访问; [5] 201711于哈尔滨工业大学深圳研究生院生物特征识别重点实验室交流访问; [6]积极组织和参加学院元旦晚会等; 5)       被哈尔滨工业大学深圳研究生院录取为2018级博士研究生。  |