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Name:WANG Huiwen
Tel No.:82338143  
Email: wanghw@vip.sina.com
Title: Professor
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Ph.D., Beihang University (Beijing University of Aeronautics & Astronautics), 1992

DEA MASE, Paris XI, 1989

B.Sc., Beihang University, 1982


WANG Huiwen is professor and Ph.D. supervisor of statistics, director of Academic Committee of SEM, director of Beijing Key Laboratory of Emergency Support Simulation Technologies for City Operations, director of Beijing Experimental Teaching Demonstration Center for Innovative Economy and Intelligent Management, director of Research Center of Complex Data Analysis in Beihang University.

Prof. Wang teaches and conducts research in the areas of complex data analysis. She has hosted 3 projects of Aviation Basic Science Foundation, 2 projects of Beijing Natural Science Foundation, project of Doctoral Program Foundation of the Ministry of Education, the French international cooperation project and more than 20 projects of Natural Science Foundation of China (NSFC) including National 863 Project and Major Project of International Cooperation and Research. She has published 5 monographs and over 150 papers.

She has won National Science Fund for Distinguished Young Scholoars and received the special government subsidy of the State Council. She is a standing committee of the 10th, 11th, 12th Beijing Municipal People's Political Consultative Conference, deputy director of the 11th, 12th Beijing Municipal Committee of CPPCC proposals. She is also a member of ISI and IASC, standing director of Statistical Education Society of China, a member of National Statistics Teaching Materials Review Committee, standing director of Chinese Research Council of Modern Management, a member of Chinese Big Data Expert Committee, a member of NSFC discipline appraisal group. Additionally, she is the member of China Democratic National Construction Association Central Committee and Democratic National Construction Association. She was awarded Beijing March-eighth red-banner pacesetter title at 2002 and 2004, the national March-eighth red-banner pacesetter title at 2004, Beijing moral standard teacher at 2012 and Beijing excellent moral education worker at 2014. She used to be visiting Professor and visiting scholar in Higher Business School in France, French National Automated Information Research Institute and University of Hong Kong.


Applied Statistics (for Undergraduate students)

Quantitative Analysis & Management Decision (for EMBA)

Management Statistics (for MBA)

Comprehensive course of Management Science & Engineering (for Ph.D.)

Research Directions

Theories, methodologies and applications of complex data analysis in the field of economics and management

Master Papers and Publications

1.Wang Huiwen, Meng Jie. Methodologies for Variable Selection, Model Classification and Automatic Modeling [M]. Beijing : Science Press, 2013.

2.V.Esposito Vinzi, W.W.Chin, J.Henseler, H.Wang. Handbook of Partial Least Square:Concepts, Methods and Application[M]. Springer, 2009.

3.Wang Huiwen, Wu Zaibin, Meng Jie. Partial least-squares methods of linear and nonlinear regression[M]. Beijing: National Defence Industry Press, 2006. (in Chinese)

4.Wang Huiwen. Partial least squares regression method and its applications[M]. Beijing : National Defence Industry Press, 1999.

5.Ren Ruoen, Wang Huiwen. Multiple data analysis - theory, methods, examples[M]. Beijing: National Defence Industry Press, 1997. (in Chinese)

6.H.Wang, M.Chen, X.Shi, and N.Li. Principal Component Analysis for Normal-Distribution-Valued Symbolic Data, IEEE Transactions on Cybernetics. 2016, 46(2): 356-365.

7.H. Wang, C. Wang, H.Zheng, H.Feng, R.Guan, W.Long. Updating Input-Output Tables with Benchmark Table Series, Economic Systems Research, 2015,27(3): 287-305.

8.H.Wang, L.Shangguan, R.Guan. Principal Component Analysis for Compositional Data Vectors. Computational Statistics. 2015, 30(4):1079-1096.

9.L. Huang, H. Wang, H. Cui, S. Wang. Sieve M-estimator for a Semi-functional Linear Model. Science China-Mathematics, 2015,58(11):2421-2434.

10.M. Chen, H. Wang, Z. Qin. Principal Component Analysis for Probabilistic Symbolic Data: a More Generic and Accurate Algorithm. Advances in Data Analysis and Classification. 2014. 2015, 9(1):59-79.

11.L. Huang, H. Wang, A. Zheng. The M-estimator for Functional Linear Regression Model. Statistics & Probability Letters, 2014, 88: 165-173.

12.H. Wang, L. Shangguan, J. Wu, R. Guan. Multiple linear Regression Modeling for Compositional Data. Neurocomputing, 2013,:122, 490-500.

13.M. Chen, H. Wang. Principal Component Analysis of Functional Data based on Constant Numerical Characteristics. Revue des Nouvelles Technologies de l'Information, Advances in Theory and Applications of High Dimensional and Symbolic Data Analysis, RNTI-E-25, 2013:138-154.

14.R. Guan, Y. Lechevallier, H. Wang. Adaptive Dynamic Clustering Algorithm for Interval-valued Data based on Squared-Wasserstein Distance. Revue des Nouvelles Technologies de l'Information, Advances in Theory and Applications of High Dimensional and Symbolic Data Analysis, RNTI-E-25, 2013: 15-30.

15.Wang Huiwen, Xia Bang, Meng Jie. Fast Gram-Schmidt Regression Method[J], Journal of Beijing University of Aeronautics and Astronautics, 2013, 39(09): 1259-1262.

16.Shangguan Liying, Wang Huiwen. Fisher discriminant method for multiple compositional-data variables in Simplex space[J]. Journal of Beijing University of Aeronautics and Astronautics, 2013. 39(10):1376-1380,1391.

17.H.Wang, R.Guan, J.Wu. CIPCA: Complete-information-based Principal Component Analysis for Interval-valued Data. Neurocomputing, 2012, 86: 158-169.

18.H.Wang, R.Guan, J.Wu, Linear Regression of Interval-valued Data based on Complete Information in Hypercubes. Journal of Systems Science and Systems Engineering. 2012, 21(4) : 422-442.

19.Wang Huiwen,Yi Bin,Ye Ming. Variable selection based on principal basis analysis[J]. Journal of Beijing University of Aeronautics and Astronautics, 2008, 34(11): 1288-1291. (in Chinese)

20.Zhang Yin, Wang Yan, Wang Huiwen. Evaluating of academic journals in management of key academic journal fund: An application of simplified principal component analysis based on interval data. Journal of Management Sciences in China, 2010, 13(7): 88-94. (in Chinese)

21.W. Long,M.K.Mok,Y. Hu,H. Wang.The Style and Innate Structure of the Stock Markets in China,Pacific-Basin Finance Journal. 2009, 17(2):224-242 .

22.Wang Huiwen, Ye Ming, Saporta Gilbert. Classification for Multiple Linear Regression Methods[J]. Journal of System Simulation, 2009, 21(22): 7048-7056. (in Chinese)

23.Wang Huiwen, Meng Jie. Predictive modeling on multivariate linear regression[J]. Journal of Beijing University of Aeronautics and Astronautics, 2007, 33(4): 500-504. (in Chinese)

24.H. Wang, Q.Liu, M.K.Mok, L.Fu,, W.M.Tse, A Hyperspherical Transformation Forecasting Model for Compositional Data, European Journal of Operational Research, 2007, 179, 459-468.

25.Z. Huang, W. Cheung, H. Wang, Cone Dominance and Efficiency in DEA,Annals of Operational Research, 2006, 145(1): .89-103.

26.M.Chavent, Y. Ding, L. Fu, H. Stolowy, H. Wang, Disclosure and Determinants Studies: An Extension Using the Divisive Cluster Method(DIV),European Accounting Review, 2005, 14(0):001-38.

27.H. Wang, Q. Liu, Y. Tu: Interpretation of Partial Least-Squares Regression Models with VARIMAX Rotation. Computational Statistics & Data Analysis 2005,48(1): 207-219

28.H.Wang,L.Fu, Y. Lechevallier, Disaster Pattern of Flood and Waterlog in Poyang Lake, Italian Journal of Applied Statistics, 2001, 13(2):P141-157

29.H.Wang, Q.Liu, Forecast Modeling For Rotations of Principal Axes of Multi-Dimensional Data Set, Computational Statistics & Data Analysis, 1998, 27(3):345-354.

30.H.Wang. Analyse et Prevision des Economies Urbaines en China (1987—1991), La Revue de Modulad ,1997,No 19:19- 44.