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Profile

Name:Wang Shanshan
Tel No.:
Email:sswang@buaa.edu.cn
Title: Assistant Professor
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Wang Shanshan  PhD(Statistics)

AssistantProfessor(Quantitative Economics and Business Statistics)

Master's Supervisor

Email: sswang@buaa.edu.cn

Office: A931

Research Areas:

High-dimensional data analysis; Non-parametric statistical analysis; Machine Learning; Survival data analysis;Statistical algorithm and applications

lEducation Background:

PhD Statistics Beijing Normal University 2011/09-2014/07

Master Statistics Beijing Normal University 2008/09-2011/07

Bachelor Applied Mathematics Qingdao University 2004/09-2008/07

Oversea Background:

Post-doc Statistics Nanyang Technology University Singapore

2014/08-2015/12

ResearchAssociate Statistics Nanyang Technology University Singapore

2013/09-2014/05

Work Experience:

Lecturer Quantitative Economics and Business Statistics BUAA-SEM

2015/12-

Courses:

Master & PhD:

Advanced Economics; Statistics with applications in R; Statistics;Nonparametric and Semi-parametric Models

Undergraduate

Applied Statistics; Time Series Analysis; Non-parametric analysis

Project

1.High-dimensional Hypothesis testing based on Penalized Likelihood and Empirical Likelihood methods, National Natural Science Foundation of China (Grant No. 11701023), 2018.01-2020.12. In charge

2.Research on discriminant analysis of oil compositional data, 2018-2019. In charge

3.Research on Pesticide Residue Index and its Construction, Scientific Research Project supported by Enterprise (Grant No.KH54034101),2016—2017. In charge

4.Research on Visualization ofPesticide Residue Data, Scientific Research Project supported by Enterprise (Grant No.KH54034301)2016—2017. In charge

Selected Papers:

(See details inhttps://www.researchgate.net/profile/Shanshan_Wang24)

1.Zhichao Wang, Huiwen Wan,Shanshan Wang*(2019). Linear Mixed-Effects Model for Multivariate Longitudinal Compositional Data.Neurocomputing, Forthcoming.

2.Yang Y,Zhihong Zou, Shanshan Wang*(2019). Statistical regression modeling for energy consumption in wastewater treatment.Journal of Environmental Sciences, 75, 201-208(SCI; ESI)

3.Huiwen Wan,Jie G,Shanshan Wan,Gilbert Saport,Spatial partial least squares autoregression: Algorithm and applications (2019).Chemometrics and Intelligent Laboratory Systems, 184, 123-131(SCI; ESI)

4.Ruiping Liu, Huiwen Wan& Shanshan Wang* (2018) Functional variable selection via Gram–Schmidt orthogonalization for multiple functional linear regression,Journal of Statistical Computation and Simulation, 88:18, 3664-3680(SCI; ESI)

5.Yuan Wei, Huiwen Wang, Shanshan Wang* & Gilbert Saporta (2018). Incremental modelling for compositional data streams,Communications in Statistics - Simulation and Computation, DOI:10.1080/03610918.2018.1455870

6.Haitao Zheng, Jie Hu, Shanshan Wang* & Huiwen Wang (2019). Examining the influencing factors of CO2 emissions at city level via panel quantile regression: evidence from 102 Chinese cities,Applied Economics incorporating Applied Financial Economics. Forthcoming

7.Yang Yu, Zhihong Zou, Shanshan Wang (2018). Bayesian quantile regression and variable selection for partial linear single-index model: Using free knot spline,Communications in Statistics - Simulation and Computation, DOI:10.1080/03610918.2017.1414248

8.Wang Shanshan and Xiang Liming*(2017). Penalized empirical likelihood inference for sparse additive hazards regression with a diverging number of covariates.Statistics and Computing,27(5): 1347-1364 (SCI; ESI)

9.Wang Shanshan and Xiang Liming* (2017). Two-layer EM-algorithm for ALD mixture regression models: A new solution to composite quantile regression.Computational Statistics & Data Analysis, 115, 136-154 (SCI; ESI)

10.Wang Shanshan and Cui Hengjian*(2017). Partial penalized empirical likelihood ratio test under sparse case.Acta Mathematica Applicatae Sinica(English Series), 32(2): 327-344(SCI; ESI)

11.Yuan Wei, Shanshan Wang* and Huiwen Wang (2017). Interval-valued data regression using partial linear model.Journal of Statistical Computation and Simulation, 87(16): 3175-3194 (SCI; ESI)

12.Huiwen Wang, Jie Gu and Shanshan Wang* (2017). An effective intrusion detection framework based on SVM with feature augmentation.Knowledge-Based Systems,136:130-139(SCI; ESI)

13.Wang Shanshan, Hu Tao* and Cui Hengjian (2016). Adjusted empirical likelihood inference for additive hazards regression.Communication in Statistics,45:24,7294-7305(SCI; ESI)

14.Wang Shanshan and Cui Hengjian (2016). Empirical Likelihood Inference for Partially Linear Errors-in-Variables models with covariate data missing at random.Acta Mathematica Applicatae Sinica(English series), 32(2), 305-318. (SCI; ESI)

15.Wang Shanshan, Cui Hengjian*and Li, Runze (2013). Empirical Likelihood Inference for Semi-parametric Estimating Equations.Science China Mathematics, 56, 1247–1262. (SCI; ESI)

16.Wang Shanshan and Cui Hengjian* (2013). Partial penalized likelihood ratio test under sparse case.Statistics, (arXiv:1312.3723)

17.Zhou Jiantao, Wang Shanshan*, Zhou Jianbo and Xu Yanli (2017). Measurement of the severity of opportuneistic fraud in personal injury insurance: evidence from China.Emerging Markets Finance and Trade,53(2): 387-399 (SCI; ESI)

18.Shanshan Wang, Tianhao Zhao, Haitao Zheng, Jie Hu (2017).The STIRPAT Analysis on Carbon Emission in Chinese Cities: An Asymmetric Laplace Distribution Mixture Model.Sustainability9(12), 2237

19.Peng, Mengjiao and Xiang, Liming*and Wang, Shanshan(2018).Semiparametric regression analysis of clustered survival data with semi-competing risks,Computational Statistics & Data Analysis, 124:53-70

20.Zheng Haitao, Hu Jie, Guan Rong* and Wang Shanshan (2016). Examining Determinants of CO2 Emissions in 73 Cities in China.Sustainability, 8(12), 1296.

21.Zhou Jiantao, Ai Jing, Wang Shanshan and Wang Tianyang (2016).Economic and Non-economic Losses Claim Effects on the Severity of Opportunistic Fraud in Auto Bodily Injury Compulsory Liability (BICL) Insurance: Evidence from China.7th China International Conference on Insurance and Risk Management (CICIRM), 358-397 (ISTP)

22.Wang Shanshan, Han Lijuan*, Cui Hengjian and Yang Hua (2011). Study on the Soil Moisture Predictive Model Based on the Precipitation in North China.Journal of Applied Meteorological Science, 22(4), 445–452.

Journal Referee

Knowledge-Based Systems

Computational Statistics & Data Analysis

Statistical Papers

Journal of Statistical Computation and Simulation

Communications in Statistics-Simulation and Computation

Selected Presentations

  • The 9thInternational Conference on PLS and Related Methods, Macau, China 2017

  • International Conference on Energy Finance, Hangzhou, 2017

  • The 10thICSA International Conference, Shanghai, 2016

  • International Workshop on Advances in Data Science, Beijing, 2016

  • The2thInternational Symposium on Interval Data Modelling: Theory and Applications, Xiamen, 2016

  • The1stInternational Conference onBig Data & Applied Statistics,Beijing, 2014

  • The16thand17th5.4 Youth Meeting of Probability and Statistics in Beijing-Tianjin Area, Beijing, 2012 and 2013

  • The 9thAnnual Probability and Statistics, Tianjin, 2010

Selected Awards

  • Zhong Jiaqing Outstanding PaperAward,2012

  • Excellent Academic Scholarship,2004-2008,2010,2013,2014

  • Excellent Graduate Student, 2012

  • The Second Race Scholarship, 2010

  • Excellent Student Cadres, 2010

  • The 6thNational Post-Graduate Mathematic Contest in Modeling, Third Prize, 2010

  • National Scholarship (Twice), 2005, 2006