Personal Information
Guoqiang Wang

College of Fundamental Studies, Shanghai University of Engineering Science, Shanghai, China

Guoqiang Wang
Educations
From 09/2005 to 07/2009, Doctorate , CHINA
From 09/2002 to 07/2005, Master , CHINA
Work Experiences
From 01/2014 to present, Professor , Shanghai University of Engineering Science
From 07/2005 to 12/2013, Assistant / Lecturer / Associate Professor , Shanghai University of Engineering Science
Projects
From 01/2015 to 12/2018, Interior-Point Algorithms for Nonlinear Symmetric Cone Programming and Applications in Optimal Control , The National Natural Science Foundation of China
From 01/2011 to 12/2013, Interior-Point Algorithms for Symmetric Cone Complementarity Problems and its Applications in Wireless Sensor Network Localization , The National Natural Science Foundation of China
Speciality
Interior-Point Methods
Symmetric Cone Optimization
Symmetric Cone Complementarity Problems
Optimization Theory, Methods and Applications
Operations Research and Cybernetics
Journal Articles
A generalization of the Craig-Sakamoto theorem to Euclidean Jordan algebras
A note on an inequality involving Jordan product in Euclidean Jordan algebras
Improved complexity analysis of full Nesterov-Todd step feasible interior-point method for symmetric optimization
New complexity analysis of a full-Newton step feasible interior-point algorithm for $P_*(\kappa)$-LCP
A full-Newton step feasible interior-point algorithm for $P_*(\kappa)$-linear complementarity problem
A full Nesterov-Todd step feasible interior-point method for convex quadratic optimization over symmetric cone
Full Nesterov-Todd step feasible interior-point method for the Cartesian $P_*(\kappa)$-SCLCP
A new full Nesterov-Todd step primal-dual path-following interior-point algorithm for symmetric optimization
A class of polynomial interior-point algorithms for the Cartesian P-matrix linear complementarity problem over symmetric cones
A unified kernel function approach to primal-dual interior-point algorithms for convex quadratic SDO
Honors and Awards
Winner of the Outstanding Achievements (Dissertation) of Graduate Students in Shanghai in 2010
Invited Talks
Kernel-based interior-point methods for the Cartesian $P_*(\kappa)$-LCP over symmetric cones
Full-Newton step feasible interior-point methods for $P_*(\kappa)$-linear complementarity problem
New complexity analysis of improved full Nesterov-Todd step feasible interior-point method for symmetric optimization
Full Nesterov-Todd step feasible interior-point methods for symmetric cone optimization