林炳清
  • 教育程度:博士及以上

  • 职称:副教授

  • 电话:86534154

  • 邮箱:bqlin@szu.edu.cn

  • 地址:汇星楼1416

教程程度 博士及以上 职称 副教授
电话 86534154 邮箱 bqlin@szu.edu.cn
地址 汇星楼1416 教育经历 2009/08 ~ 2014/02,新加坡南洋理工大学,数理科学学院,统计学,博士  
2003/09 ~ 2007/07,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  
2005/03 ~ 2007/07,电子科技大学,管理学院,金融学双学位
工作经历 2021/01 ~ 至今,深圳大学,数学与统计学院, 副教授  
2014/09~ 2020.12,深圳大学,数学与统计学院, 讲师
研究领域 生物统计、模型选择
获得荣誉 深圳市海外高层次人才C类
教学课程 深度学习、数据挖掘、统计计算与软件、概率论与数理统计
科研成果 <p>
1. Lin, B., Pang, Z., Zhang, J., Chen, C., Fast feature selection via streamwise procedure for massive data. Brazilian Journal of Probability and Statistics, 36(1): 81-102, 2022.  <br>2. Zhang, J., Lin, B.*, Estimation of correlation coefficient with general distortion measurement errors. Communications in Statistics - Simulation and Computation, 1-31, 2021. <br>3. Lin, B. and Pang, Z., Stability of methods for differential expression analysis of RNA-seq data. BMC genomics, 20:35 2019.  <br>4. 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.  <br>5. Zhang, J., Gai, Y., Lin, B.* and Zhu, X., Nonlinear regression models with single-index heteroscedasticity. Statistica Neerlandica, 73(2), 292-316, 2019. 6. Lin, B., Pang, Z. and Wang, Q., Cluster feature selection in high dimensional linear models. Random Matrices: Theory and Applications, <br>6: (1750015-1)-(1750015-23), 2018.  <br>7. 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.  <br>8. 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. <br>9. Lin, B., Wang, Q., Zhang, J. and Pang, Z., Stable prediction in high-dimensional linear models. Statistics and Computing, 27:1401-1412, 2017.  <br>10. Pang, Z., Lin, B. and Jiang J., Regularization parameter selection via bootstrapping. Australian & New Zealand Journal of Statistics, 58:335-356, 2016.<br><br></p>
科研项目 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, 23万,主持  <br>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, 3万,主持"<br>

个人简介

著有《深度学习入门与TensorFlow实践》,发表SCI论文30余篇,主持并参与多项国家自然科学基金

教育经历

  • 2009/08 ~ 2014/02,新加坡南洋理工大学,数理科学学院,统计学,博士 2003/09 ~ 2007/07,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 2005/03 ~ 2007/07,电子科技大学,管理学院,金融学双学位

工作经历

  • 2021/01 ~ 至今,深圳大学,数学与统计学院, 副教授 2014/09~ 2020.12,深圳大学,数学与统计学院, 讲师

研究领域

  • 生物统计、模型选择

获得荣誉

  • 深圳市海外高层次人才C类

教学课程

  • 深度学习、数据挖掘、统计计算与软件、概率论与数理统计

科研成果

  • 1. Lin, B., Pang, Z., Zhang, J., Chen, C., Fast feature selection via streamwise procedure for massive data. Brazilian Journal of Probability and Statistics, 36(1): 81-102, 2022.  
    2. Zhang, J., Lin, B.*, Estimation of correlation coefficient with general distortion measurement errors. Communications in Statistics - Simulation and Computation, 1-31, 2021.
    3. Lin, B. and Pang, Z., Stability of methods for differential expression analysis of RNA-seq data. BMC genomics, 20:35 2019.  
    4. 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.  
    5. Zhang, J., Gai, Y., Lin, B.* and Zhu, X., Nonlinear regression models with single-index heteroscedasticity. Statistica Neerlandica, 73(2), 292-316, 2019. 6. Lin, B., Pang, Z. and Wang, Q., Cluster feature selection in high dimensional linear models. Random Matrices: Theory and Applications,
    6: (1750015-1)-(1750015-23), 2018.  
    7. 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.  
    8. 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.
    9. Lin, B., Wang, Q., Zhang, J. and Pang, Z., Stable prediction in high-dimensional linear models. Statistics and Computing, 27:1401-1412, 2017.  
    10. Pang, Z., Lin, B. and Jiang J., Regularization parameter selection via bootstrapping. Australian & New Zealand Journal of Statistics, 58:335-356, 2016.

科研项目

  • 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, 23万,主持  
    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, 3万,主持"