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个人简介

教育经历 2011南加州大学博士 2007明尼苏达州德卢斯大学硕士 2005复旦大学硕士 2003复旦大学学士 工作经历 2014-北京大学数学科学学院助理教授 2011-2014宾夕法尼亚大学佩雷尔曼医学院卫生统计与流行病学系博士后 主讲课程 高等统计学,高等统计学II,应用回归分析,大数据的时空统计特性,高维数据分析与统计推断 指导研究生 孙浩然(16博),赵芯(16博),陈春滔(16硕),颜彬(16硕),张希(16硕),郑一荻(16硕),崔畅(17博)

研究领域

My research interests lie in the broad areas of high-dimensional statistics and statistical machine learning, with particular emphasis on compositional data analysis and statistical learning from high-dimensional complex data. I am also interested in causal inference, survival analysis, and applications of statistical and machine learning methods to genomics, metagenomics, and environmental science.

近期论文

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Zheng, Z., Lv, J. and Lin, W. (2020). Nonsparse learning with latent variables. Operations Research, to appear. [PDF] [Supplement] Zhang, S., Chen, S., Guo, B., Wang, H. and Lin, W. (2020). Regional air-quality assessment that adjusts for meteorological confounding (in Chinese). Scientia Sinica Mathematica, 50, 527–558. Zhang, J. and Lin, W. (2019). Scalable estimation and regularization for the logistic normal multinomial model. Biometrics, 75, 1098–1108. [PDF] [Supplement] [Software] Uematsu, Y., Fan, Y., Chen, K., Lv, J. and Lin, W. (2019). SOFAR: Large-scale association network learning. IEEE Transactions on Information Theory, 65, 4924–4939. [PDF] Cao, Y., Lin, W. and Li, H. (2019). Large covariance estimation for compositional data via composition-adjusted thresholding. Journal of the American Statistical Association, 114, 759–772. [PDF] Cao, Y., Lin, W. and Li, H. (2018). Two-sample tests of high-dimensional means for compositional data. Biometrika, 105, 115–132. [PDF] Strazza, M., Pirrone, V., Wigdahl, B., Dampier, W., Lin, W., Feng, R., Maubert, M. E., Weksler, B., Romero, I. A., Couraud, P.-O. and Nonnemacher, M. R. (2016). Prolonged morphine exposure induces increased firm adhesion in an in vitro model of the blood–brain barrier. International Journal of Molecular Sciences, 17, 916. Lin, W., Feng, R. and Li, H. (2015). Regularization methods for high-dimensional instrumental variables regression with an application to genetical genomics. Journal of the American Statistical Association, 110, 270–288. [PDF] [Supplement] [Software] Healy, F., Lin, W., Feng, R., Hanna, B. D., Hedrick, H. and Panitch, H. B. (2015). An association between pulmonary hypertension and impaired lung function in infants with congenital diaphragmatic hernia. Pediatric Pulmonology, 50, 672–682. Cantu, E., Shah, R. J., Lin, W., Daye, Z. J., Diamond, J. M., Suzuki, Y., Ellis, J. H., Borders, C. F., Andah, G. A., Beduhn, B., Meyer, N. J., Ruschefski, M., Aplenc, R., Feng, R. and Christie, J. D. for the Lung Transplant Outcomes Group Investigators (2015). Oxidant stress regulatory genetic variation in recipients and donors contributes to risk of primary graft dysfunction after lung transplantation. Journal of Thoracic and Cardiovascular Surgery, 149, 596–602. [Editorial Commentary] Lin, W., Shi, P., Feng, R. and Li, H. (2014). Variable selection in regression with compositional covariates. Biometrika, 101, 785–797. [PDF] [Supplement] [Software] Sun, H., Lin, W., Feng, R. and Li, H. (2014). Network-regularized high-dimensional Cox regression for analysis of genomic data. Statistica Sinica, 24, 1433–1459. [PDF] [Supplement] Lin, W. and Lv, J. (2013). High-dimensional sparse additive hazards regression. Journal of the American Statistical Association, 108, 247–264. [PDF] [Software] Lin, W. (2009). Asymptotic behavior of periodic Cohen-Grossberg neural networks with delays. Neural Computation, 21, 3444–3459. [PDF] Lin, W. and Chen, T. (2007). Dynamics of periodic Lotka–Volterra systems with general time delays. Dynamics of Continuous, Discrete and Impulsive Systems, Series B, 14, 885–901. Lin, W. and Chen, T. (2006). Analysis of two restart algorithms. Neurocomputing, 69, 2301–2308. Lin, W. and Chen, T. (2005). Controlling chaos in a chaotic neuron model. International Journal of Bifurcation and Chaos, 15, 2611–2621. Lin, W. and Chen, T. (2005). Positive periodic solutions of delayed periodic Lotka–Volterra systems. Physics Letters A, 334, 273–287.

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