基本情况

王国强，理学博士学位，现任上海工程技术大学教授、硕士生导师，数理与统计学院院长。现主持国家自然科学基金面上项目。曾主持完成国家自然科学基金面上项目、国家自然科学青年科学基金、中国博士后特别资助、上海市自然科学基金和教育部留学回国人员科研启动基金等科研项目。出版学术专著1部，在国内外学术期刊发表科研论文60余篇，其中SCI收录50余篇。上海市育才奖获得者。获上海市优秀研究生成果（学位论文）暨上海市优秀博士学位论文，上海市科学技术进步奖三等奖等。


研究领域

最优化算法与应用、对称锥优化、统计优化、高维数据统计推断、金融统计、机器学习等

教育背景

2005年至2009年博士，上海大学

2002年至2005年硕士，上海大学

2000年至2002年学士，山东师范大学


工作经历

2014年至今教授，上海工程技术大学

2012年至2013年访问学者，澳大利亚科廷大学

2010年至2013年博士后，上海师范大学

2009年至2013年副教授，上海工程技术大学

2007年至2009年讲师，上海工程技术大学

2005年至2007年助教，上海工程技术大学


论文发表

  1. Z.Y. Dai, J.J. Yi, L. Yan, Q.W. Xu, L. Hu, J.H. Li, and G.Q. Wang. PFEMed: Few-shot medical image classification using prior guided feature enhancement. Pattern Recognition, October 9, 2022.已录用
  2. X.J. Xie, K.Y. Luo, G.Q. Wang*. A new L1 multi-kernel learning support vector regression ensemble algorithm with AdaBoost. IEEE Access, 10: 20375-20384, 2022.
  3. X.N. Chi, G.Q. Wang*. A full-Newton step infeasible interior-point method for the special weighted linear complementarity problem. Journal of Optimization Theory and Applications, 190(1):108-129, 2021.
  4. 谢晓金,罗康洋,张怡,金建炳, Lin Haixiang,殷志祥,王国强*.基于非线性组合动态传播率模型的我国COVID-19疫情分析与预测，运筹学学报，2021, 25(1):17-30.
  5. J. Tao, G.Q. Wang, and L.C. Kong. The Araki-Lieb-Thirring inequality and the Golden-Thompson inequality in Euclidean Jordan algebras. Linear and Multilinear Algebra, 2021.https://doi.org/ 10.1080/ 03081087. 2021. 1873230
  6. M. Xu, J.B. Jin, G.Q. Wang, A. Segers, T. Deng, and H.X. Lin. Machine learning based bias correction for numerical chemical transport models. Atmospheric Environment, 248:118022 (10 pp), 2021.
  7. L. Li, J.Y. Tao, M. El Ghami, X.Z. Cai, and G.Q. Wang*. A new parametric kernel function with a trigonometric barrier term for P*(k)-linear complementarity problems. Pacific Journal of Optimization, 13(2): 255-278, 2017.
  8. C.J. Yu, Q. Lin, R. Loxton, K.L. Teo, and G.Q. Wang. A hybrid time-scaling transformation for time-delay optimal control problems. Journal of Optimization Theory and Applications, 169(3):876-901, 2016.
  9. G.Q. Wang, J. Tao, and L.C. Kong. A note on an inequality involving Jordan product in Euclidean Jordan algebras. Optimization Letters, 10(4): 731-736, 2016.
  10. 10. J. Tao and G.Q. Wang. A generalization of the Craig-Sakamoto theorem to Euclidean Jordan algebras. Linear Algebra and its Applications, 493(1): 134-145, 2016.
  11. G.Q. Wang*, L.C. Kong, J.Y. Tao, G. Lesaja. Improved complexity analysis of full Nesterov-Todd step feasible interior-point method for symmetric optimization, Journal of Optimization Theory and Applications, 2015, 166(2): 588-604.
  12. G.Q. Wang*, Y.Q. Bai, X.Y. Gao, D.Z. Wang. Improved complexity analysis of full Nesterov-Todd step interior-point methods for semidefinite optimization, Journal of Optimization Theory and Applications, 2015, 165(1): 242-262.
  13. G.Q. Wang*, X.J. Fan, D.T. Zhu and D.Z. Wang. New complexity analysis of a full-Newton step feasible interior-point algorithm for P*(k)-LCP. Optimization Letters, 9(6):1105-1119, 2015.
  14. G.Q. Wang*, C.J. Yu, K.L. Teo. A full-Newton step feasible interior- point algorithm for P*(k)-linear complementarity problem, Journal of Global Optimization, 2014, 59(1): 81-99, 2014.
  15. G.Q. Wang*, C.J. Yu and K.L. Teo. A new full Nesterov-Todd step feasible interior-point method for convex quadratic optimization over symmetric cone. Applied Mathematics and Computation, 221(15): 329-343, 2013.
  16. G.Q. Wang* and G. Lesaja. Full Nesterov-Todd step feasible interior-point method for the Cartesian P*k)-SCLCP. Optimization Methods and Software, 28(3): 600-618, 2013.
  17. X.Z. Cai, G.Q. Wang* and Z.H. Zhang. Complexity analysis and numerical implementation of primal-dual interior-point methods for convex quadratic optimization based on a finite barrier. Numerical Algorithms, 62(2): 289-306, 2013.
  18. G.Q. Wang*, Y.Q. Bai. A class of polynomial interior-point algorithms for the Cartesian P-matrix linear complementarity problem over symmetric cones, Journal of Optimization Theory and Applications, 2012, 152(3): 739-772.
  19. G.Q. Wang* and Y.Q. Bai. A new full Nesterov-Todd step primal-dual path-following interior-point algorithm for symmetric optimization. Journal of Optimization Theory and Applications, 154(3): 966-985, 2012.
  20. G. Lesaja, G.Q. Wang and D.T. Zhu. Interior-point methods for Cartesian P*(k)-linear complementarity problems over symmetric cones based on the eligible kernel functions. Optimization Methods and Software, 27(4-5): 827-843, 2012.
  21. G.Q. Wang*. A new polynomial interior-point algorithm for the monotone linear complementarity problem over symmetric coneswith full NT-steps. Asia-Pacific Journal of Operational Research, 29(2): 1250015 (20pp), 2012.
  22. G.Q. Wang* and D.T. Zhu. A unified kernel function approach to primal-dual interior-point algorithms for convex quadratic SDO. Numerical Algorithms, 57(4): 537-558, 2011.
  23. Y.Q. Bai, G. Lesaja, C. Roos, G.Q. Wang and M. Ghami. A class of large-update and small-update primal-dual interior-point algorithm for linear optimization. Journal of Optimization Theory and Application, 138(3): 341-359, 2008.
  24. Y.Q. Bai and G.Q. Wang. Primal-dual interior-point algorithms for second-order cone optimization based on a new parametric kernel function. Acta Mathematica Sinica, English Series, 23(11): 2027-2042, 2007.
  25. G.Q. Wang, Y.Q. Bai, and C. Roos. Primal-dual interior-point algorithms for semidefinite optimization based on a simple kernel function. Journal of Mathematical Modelling and Algorithms, 4(4): 409-433, 2005.



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