Dr Yu Guang

Dr Yu Guang Wang

Level A Research, Research Officer

College of Science, Health and Engineering

School of Engineering and Mathematical Sciences

Department of Mathematics and Statistics

Room 203, Physical Sciences 1 Building, Melbourne (Bundoora)


PhD (UNSW Australia)



Membership of professional associations

Member Aust Math Soc, ANZIAM, SIAM

Area of study

Mathematics and Statistics

Brief profile

I am a post-doctor in La Trobe University, Melbourne. Before that I was a one-year postdoctoral fellow in City University of Hong Kong in 2015-2016 and a half-year research assistant in University of New South Wales, Australia in 2015. I obtained my PhD in UNSW Australia under the supervision of Prof Ian Sloan, A/Prof Robert Womersley and Prof Michael Cowling and Master and Bachelor Degrees both from China Jiliang University.

I am interested in computational mathematics, stochastic analysis and machine learning, in particular, in the following areas.

  • Applied and Computational Harmonic Analysis
  • Monte Carlo and Quasi-Monte Carlo Methods on Manifolds
  • Computational Statistics and Stochastic Computation
  • Machine Learning
  • Computer Graphics

Research specialisation

- Numerical methods

- Statistical modelling

Recent publications


  • Q. T. Le Gia, I. H. Sloan, Y. G. Wang, R. S. Womersley. Needlet approximation for isotropic random fields on the sphere. J. Approx. Theory, 216:86-116, 2017. arXiv


  • J. S. Brauchart, E. B. Saff, I. H. Sloan, Y. G. Wang, R. S. Womersley. Random point sets on the sphere — Hole radii, covering, and separationExp. Math., 2016. arXiv
  • Y. G. Wang, I. H. Sloan, R. S. Womersley. Riemann localisation on the sphereJ. Fourier Anal. Appl., 2016. arXiv
  • Y. G. Wang, Quoc T. Le Gia, I. H. Sloan, R. S. Womersley. Fully discrete needlet approximation on the sphereAppl. Comput. Harmon. Anal., 2016. arXiv
  • Y. G. Wang. Filtered polynomial approximation on the sphereBull. Aust. Math. Soc., 93(01): 162–163, 2016. PDF
  • F. Cao, D. Wang, H. Zhu, Y. G. Wang. An iterative learning algorithm for feedforward neural networks with random weightsInform. Sci., 328: 546–557, 2016. PDF


  • J. S. Brauchart, J. Dick, E. B. Saff, I. H. Sloan, YG. Wang, R. S. Womersley. Covering of spheres by spherical caps and worst-case error for equal weight cubature in Sobolev spacesJ. Math. Anal. Appl., 431(2):782–811, 2015. arXiv


  • Y. G. Wang, F. Cao. Approximation by semigroup of spherical operatorsFront. Math. China, 9(2):387–416, 2014. PDF
  • Z. Chen, H. Zhu, Y. G. Wang. A modified extreme learning machine with sigmoidal activation functionsNeural Comput. Appl., 22(3-4):541–550, 2013. PDF
  • Y. Yuan, Y. G. Wang, F. Cao. Optimization approximation solution for regression problem based on extreme learning machineNeurocomputing, 74(16):2475–2482, 2011. PDF
  • Y. G. Wang, F. Cao, Y. Yuan. A study on effectiveness of extreme learning machineNeurocomputing, 74(16):2483–2490, 2011. arXiv
  • Y. G. Wang, F. Cao. Approximation by Boolean sums of Jackson operators on the sphereJ. Comput. Anal. Appl., 13(5):830–842, 2011. arXiv
  • Y. G. Wang, F. Cao. The direct and converse inequalities for Jackson-type operators on spherical capJ. Inequal. Appl., Art. ID 205298, 16 pages, 2009. arXiv


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