Institute of High Performance Computing


People: Vibrant & Dynamic Culture



Computing Science (CS)

Dr. LI Guoqi

Dr. LI Guoqi

Research Interests:

  •  Complex networks and optimization
  •  System identification
  •  Cognitive memory


  • Doctor of Philosophy (P.h.D)   Nanyang Technological University, School of Electrical and Electronic Engineering, Singapore,   07/2007-08/2011
  • Master of Engineering (M.E.) Xi’an Jiaotong University, School of Electronic and Information Engineering, P.R. China,    09/2004-07/2007
  • Bachelor of Engineering (B.E.)   Automation, Xi’an University of Technology, P.R. China, 09/2000-07/2004

Published Journals/ Articles:


    • G. Li, N. Ning, K. Ramanathan, H. Wei, L. Pan and Liu Shi, “Behind the Magical Numbers: Hierarchical Chunking and the Human Working Memory Capacity”, International Journal of Neural Systems, Accepted, 2013.
    • G. Li, C. Wen, Z. G. Li, A. Zhang, Y. Feng, and K. Z. Mao, “Model Based Online Learning with Kernels”,   IEEE Transactions on Neural Networks and Learning systems (IEEE TNNLS, Regular paper), vol. 24, pp. 356 - 369, 2013. 
    • G. Li, C. Wen, “Identification of Wiener Systems with Clipped Observations”, IEEE Transactions on Signal Processing (IEEE TSP, Regular paper),   vol. 60, pp. 3845 - 3852, 2012.
    • G. Li, C. Wen, “Convergence of fixed-point iteration for the identification of Hammerstein and Wiener systems”, International Journal of Robust and Nonlinear Control , Accepted, doi: 10.1002/rnc.2837, 2012.
    • G. Li, C. Wen, W. X. Zheng, and Y. Chen, “Identification of a Class of Nonlinear Autoregressive Models with Exogenous Inputs Based on Kernel Machines” , IEEE Transactions on Signal Processing ( IEEE TSP, Regular paper ) , vol. 59, No. 5, pp. 2146-2159,   2011.
    • G. Li, C. Wen, G. B. Huang, and Y. Chen: “Error tolerance based support vector machine for regression”, Neurocomputing, vol. 74, No. 5, pp. 771-782, 2011.
    •   G. Li, C. Wen, “Convergence of Normalized Iterative Identification of Hammerstein Systems”, Systems and Control Letters, vol. 60, pp. 929-935, 2011.
    •   G. Li, C. Wen, and W. X. Zheng, “A New Iterative Identification Scheme for Hammerstein Systems with Support Vector Machine Based on Biconvex Optimization”, Australian Journal of Intelligent Information Processing Systems, vol. 11, pp. 29-34, 2010.
    •   K. Ramanathan, N. Ning, D. Dhanasekar, G. Li, L. Shi and P. Vadakkepat, “Presynaptic learning and memory with a persistent firing neuron and a habituating synapse: a model of short term persistent habituation, International Journal of Neural System, vol. 22, pp. 12500151- 125001520, 2012.
    • L. ZhangA. Zhang, Z. Ren, G. Li, C. Zhang and J. Han, Hybrid adaptive robust control of static var compensator in power systems, International Journal of Robust and Nonlinear Control , Accepted, 2012.
    • Y. Chen, C. Wen, G. Tao, M. Bi, and G. Li,   “Continuous and Noninvasive Blood Pressure Measurement: A Novel Modeling Methodology of the Relationship Between Blood Pressure and Pulse Wave Velocity”, Annals of Biomedical Engineering, vol. 37, No. 11, pp. 2222-2233,   2009.
    • G. Li, G. Zhao, and Z. Sun, “Kernel Function Construction Based on Surface Reconstruction of Sample Similarity”, Information and control, vol. 36,   pp. 47-55, 2007. (In Chinese).
    •  G. Li, G. Zhao, and Z. Sun, “The Application in Classification among Fisher Discriminant Criterion, K-L Conversion and SVM”, Computer Engineering and Application, vol. 42,   pp. 147-151, 2006. (In Chinese).
    • G. Li, G. Zhao and F. Yang, “Online Learning with Kernels in Classification and Regression,"" Evolving Systems, Accepted, 2013.




    • G. Li and C. Wen, “Legendre polynomials in signal reconstruction and compression”, 5th IEEE Conference on Industrial Electronics and Applications (ICIEA), Taiwan, 2010.
    • G. Li and C. Wen, “Identification of Wiener Systems based on Fixed Point Theory”, 11th International Conference on Control, Automation, Robotics and Vision (ICARCV), Singapore, 2010.
    • G. Li, C. Wen and Z. G. Li, “A New Online Learning with Kernels Method in Novelty Detection” ,   The 37th Annual Conference of the IEEE Industrial    Electronics Society (IECON) , Melbourne, Australia, 2011.
    • G. Zhao, G. Li, C. Wen and F. Yang, “On the Convergence of normalized iterative identification of Hammerstein systems” , ICAR2011, Dubai, 2011.
    • G. Li,  C. Wen, W. X. Zheng and G. Zhao, “On the iterative identification of block-oriented systems based on biconvex optimization” , 16th IFAC Symposium on System Identification, SYSID 2012, Brussels, 2012.
    • G. Li, C. Wen, D. Cui and F. Yang, “A New Method of Online Learning with Kernels for Regression” , 7th IEEE Conference on Industrial Electronics and Applications (ICIEA), Singapore, 2012.
    • G. Li and G. Zhao, “Online Learning with Kernels in Classification and Regression,"" IEEE Conference on Evolving and Adaptive Intelligent Systems (IEEE EAIS), Madrid, Spain , 2012.
    • L. Shi, K. Ramanathan, N. Ning,    L. Pan ,   W. He , G. Li , H. Li and   Z. Yang, “The Challenges and Solutions for the Development of Artificial Cognitive Memory ,""   European Phase-Change and Ovonic Science Symposium, Tampere Finland, 2012. 
    • G. Li, N. Ning, K. Ramanathan, and L. Shi “Revised Online Learning with Kernels”, 2013 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2013), Singapore.

This page is last updated at: 09-SEP-2013