菜单总览
— 优秀师资 —

林楠

职位:

客座副教授

教育背景:

博士(美国伊利诺伊大学香槟分校)

理学硕士 (金融学,伊利诺伊大学香槟分校)

理学硕士(统计学,伊利诺伊大学香槟分校)

理学学士 (中国科技大学)

研究领域
海量数据统计计算;生物信息学;贝叶斯分位数回归;纵向数据和函数数据分析;麻醉学中的统计应用
Email

nlin@wustl.edu

个人简介:


    林楠于1999年在中国科技大学获得理学学士学位,在2000年和2003年在伊利诺伊大学香槟分校分别取得硕士和博士学位,并于2003年获取了金融学的硕士学位。在加入华盛顿大学圣路易斯分校之前,他在耶鲁大学统计基因组学和蛋白质组学中心从事博士后研究工作。他现担任华盛顿大学圣路易斯分校数学系副教授,并兼任于其医学院的生物统计学中心。他的方法性研究主要集中在海量数据统计计算、贝叶斯正则化、生物信息学以及纵向数据和函数数据分析。他的应用性研究主要集中在麻醉学和基因组学的统计分析。他教授多门统计学课程,包括数理统计、贝叶斯统计、线性模型、实验设计、统计计算,非参数统计等。此外,他担任期刊Computational Statistics & Data Analysis副主编。


学术著作:


1. Xi, R. and Lin, N. (in press), Direct regression modeling of high-order moments in big data, Statistics and Its Interface.

2. Zhang, B.*, Zhou, Y.*, Lin, N.*, Lowdon, R. F.*, Hong, C., Nagarajan, R. P., Cheng, J. B., Li, D., Stevens, M., Lee, H. J., Xing, X., Zhou, J., Sundaram, V., Gu, J., Gascard, P., Sigaroundinia, M., Tisty, T. D., Kadlecek, T., Weiss, A., O’Green, H., Farnham, P. J., Marie, C. L., Ligon, K. L., Madden, P. A. F., Tam, A., Moore, R., Hirst, M., Marra, M. A., Zhang, B., Castello, J. and Wang, T. (2013), Functional DNA methylation differences between tissues, cell types, and across individuals  discovered using the M&M algorithm, Genome Research, 23, 1522-1540. (*: co-first author)

3. Wang, G., Lin, N. and Zhang, B. (2013), Functional contour regression, Journal of Multivariate Analysis, 116, 1-13.

4. Wang, G., Lin, N. and Zhang, B. (2013), Dimension reduction in functional regression using mixed data canonical correlation analysis, Statistics and Its Interface, 6, 187-196.

5. Xu, L., Lin, N., Zhang, B. and Shi, N. (2012), A finite mixture model for working correlation matrices in generalized estimating equations, Statistica Sinica, 22(2), 755-776.

6. Avidan, M.S., Jacobsohn, E., Glick, D., Burnside, B., Zhang, L., Villafranca, A., Karl, L., Kamal, S., Torres, B., O'Conner, M., Evers, A. S., Gradwohl, S., Lin, N., Palanca, B. J. and Mashour, G. A. (2011), Prevention of intraoperative awareness in a high-risk surgical population, The New England Journal of Medicine, 365, 591-600.

7. Lin, N. and Xi, R. (2011), Aggregated estimating equation estimation, Statistics and Its Interface, 4, 73-84.

8. Li, Q., Xi, R. and Lin, N. (2010), Bayesian regularized quantile regression, Bayesian Analysis, 5,533-556.

9. Li, Q. and Lin, N. (2010), The Bayesian elastic net, Bayesian Analysis, 5,151-170.

10. Lin, N. and Xi, R. (2010), Fast surrogates of U-statistics, Computational Statistics and Data Analysis, 54, 16-24.

11. Xi, R., Lin, N. and Chen, Y. (2009), Compression and aggregation for logistic regression analysis in data cubes, IEEE Transactions on Knowledge and Data Engineering, 21(4), 479-492.

12. Woods, C. and Lin, N. (2009), Item response theory with estimation of the latent density using Davidian curves, Applied Psychological Measurement, 33,102-117.

13. Lin, N. and He, X. (2006), Robust and efficient estimation under data grouping, Biometrika, 93 (1), 99-112.

14.  Lin, N. and Zhao, H. (2005), Are scale-free networks robust to measurement errors? BMC Bioinformatics, 6: 119.

15. Lin, N., Wu, B., Jansen, R., Gerstein, M. and Zhao, H. (2004), Information assessment on predicting protein-protein interactions, BMC Bioinformatics, 5: 154.