各系部老师-林炳清
个人简介
教育经历
工作经历
研究领域
获得荣誉
教学课程
科研成果


林炳清

姓名：林炳清
职称：讲师
性别：男

教育程度：博士以上
电话：**

邮箱：bqlin@szu.edu.cn
地址：科技楼1416





简介： 林炳清博士毕业于新加坡南洋理工大学，深圳市海外高层次人才，南山区领航人才。主要研究方向为数据挖掘，机器学习，高维数据分析，生物信息学。已获得2项国家基金资助，发表论文20余篇，其中JCR一区文章5篇，JCR二区文章2篇。

教育经历： 2003年 ~ 2007年，电子科技大学，数学与应用数学学院，数学与应用数学专业，学士
2005年 ~ 2007年，电子科技大学，管理学院，金融学双学位
2009年 ~ 2014年， 新加坡南洋理工大学，数理科学学院，统计学，博士

工作经历： 2012年01月 ~ 2013年01月，Khoo Teck Puat Hospital, Singapore.，Statistic Consultant
2013年7月 ~ 2014年7月, 新加坡南洋理工大学，生物科学学院，博士后研究员
2014年9月 ~ 至今， 深圳大学，数学与统计学院，讲师

研究领域： 数据挖掘，机器学习，高维数据分析，生物信息学

获得荣誉： 深圳市海外高层次人才
南山区领航人才

教学课程： 本科生课程：数据挖掘，统计计算与模拟
研究生课程：统计软件与编程，非参数统计

科研成果： 科研项目：
1.高维回归模型集成方法研究>, 深圳大学新引进教师校科研启动项目（自然科学类），2015-2017，主持
2.海量数据下回归模型的变量选择及统计推断研究，国家自然科学基金青年科学基金，项目2018/01~2020/12, 主持
3.高维回归模型的预测稳定性研究，国家自然科学基金数学天元专项基金，2017/01~2017/12, 主持

代表性学术论文：
1. Lin, B. and Pang, Z., Stability of methods for differential expression analysis of RNA-seq data. BMC genomics, 20:35 2019. (JCR: q1, IF:3.730)
2. Zhang, J., Lin, B. * and Li, G., Nonlinear regression models with general distortion measurement errors. Journal of Statistical Computation and Simulation 89 (8), 1482-1504, 2019. (JCR:q4; IF:0.501)
3. Zhang, J., Gai, Y., Lin, B. * and Zhu, X., Nonlinear regression models with single-index heteroscedasticity, Statistica Neerlandica, 73(2), 292-316, 2019. (JCR:q4; IF:0.433)
4. Zhou, Y., Zhu, J., Tong, T., Wang, J., Lin, B. and Zhang, J., A statistical normalization method and differential expression analysis for RNA-Seq between different species. BMC bioinformatics, 20(1), 2019. (JCR:q1; IF:2.511)
5. Chen, T., Lin, B., Geng, H. and Yu, B., Sensor drift calibration via spatial correlation model in smart building. Proceedings of the 56th Annual Design Automation Conference, 2019
6. Zhang, J., Lin, B., Zhou, Y. and Zhang J., Dimension reduction regressions with measurement errors subject to additive distortion. Journal of Statistical Computation and Simulation. 88: 2631-2649, 2018. (JCR: q3; IF: 0.869)
7. Li, W., Hong, R., Lai, L., Dong, Q., Ni, P. Chelliah, R., Huq, M. Ismail, S. Chandola, U., Ang, Z., Lin, B., Chen, X., Chen, L. and Zhang, L., Genome-wide RNAi screen identify melanoma-associated antigen mageb3 involved in X chromosome inactivation. Journal of Molecular Biology. 430:2734-2746, 2018. (JCR: q1; IF: 4.894)
8. Lin, B., Pang, Z. and Wang, Q., Cluster feature selection in high dimensional linear models. Random Matrices: Theory and Applications. 6: (**-1)-(**-23), 2018. (JCR: q3; IF: 0.784)
9. Hong, R., Lin, B., Chen X., Ng, H., Zhang, K. and Zhang, L., High-resolution RNA allelotyping along the inactive X chromosome: evidence of RNA polymerase III in regulating chromatin configuration. Scientific Reports, 7: 45460, 2017. (JCR: q1; IF: 4.122)
10. Zhang, J., Zhou, Y., Lin, B.* and Yu, Y., Estimation and hypothesis test on partial linear models with additive distortion measurement errors. Computational Statistics and Data Analysis. 112:114-128, 2017. (JCR: q2; IF: 1.181)
11. Lin, B. and Yu, B., Smart Building Uncertainty Analysis via Adaptive Lasso. IET Cyber-Physical Systems: Theory & Applications. 2:42-48, 2017.
12. Zhang, J., Chen, Q., Lin, B. * and Zhou, Y., On the single-index model estimate of the conditional density function: consistency and implementation. Journal of Statistical Planning and Inference. 187:56-66, 2017. (JCR: q3; IF: 0.814)
13. Lin, B., Wang, Q., Zhang, J. and Pang, Z., Stable prediction in high-dimensional linear models. Statistics and Computing, 27:1401-1412, 2017. (JCR: q1; IF: 1.851)
14. Pang, Z., Lin, B. and Jiang J., Regularization parameter selection via bootstrapping. Australian & New Zealand Journal of Statistics, 58:335-356, 2016. (JCR: q4; IF:0.385)
15. Huang, Z., Shao, Q., Pang, Z. and Lin, B., Adaptive testing for the partially linear single-index model with error-prone linear covariates. Statistical Methodology, 21:51-58, 2015. (JCR: q3; IF:0.670)
16. Lin, B., Zhang, L. and Chen, X., LFCseq: a nonparametric approach for differential expression analysis of RNA-seq data. BMC genomics, 15:s7, 2014. (JCR: q1, IF: 3.730)
17. Lin, B. and Pang, Z., Tilted correlation screening learning in high dimensional data analysis. Journal of Computational and Graphical Statistics, 23:478-496, 2014. (JCR: q1; IF:1.790)
18. Huang, Z., Pang, Z. and Lin, B., Model structure selection in single-index-coefficient regression models. Journal of Multivariate Analysis, 125:159:175, 2014. (JCR: q3; IF:1.009)
19. Lin, B.#, Pang, Z. and Jiang, J., Fixed and random effects selection by REML and pathwise coordinate optimization. Journal of Computational and Graphical Statistics, 22:341-355, 2013. (JCR: q1; IF:1.790)
20. Huang, Z., Lin, B., Feng, F. and Pang, Z., Efficient penalized estimating method in the partially varying-coefficient single-index model. Journal of Multivariate Analysis, 114:189–200, 2013. (JCR: q3; IF:1.009)
21. Cheon, G., Siddiqui,S., Lim, T., Seet,E., Lin, B., Palaniappan, S. and Koh, K., Thinking twice before using the LMA for obese and older patients-A prospective observational study. Journal of Anesthesia and Clinical Research, 2013.
* 杂志影响因子和JCR分区均来源于Web of Science，2019
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