Researcher

Dr Yu Guang Wang

Field of Research (FoR)

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Biography

I am a postdoctoral fellow in School of Mathematics and Statistics in UNSW Sydney. Before that, I was a postdoctoral fellow in ICERM, Brown University in Feb 2018 to May 2018. I was an ARC Research Fellow in Statistics in La Trobe University, Melbourne in Sep 2016 to Jan 2018. I was a one-year postdoctoral fellow in City University of Hong Kong in Oct 2015 to Aug 2016 and a half-year research assistant in University of New South Wales,...view more

I am a postdoctoral fellow in School of Mathematics and Statistics in UNSW Sydney. Before that, I was a postdoctoral fellow in ICERM, Brown University in Feb 2018 to May 2018. I was an ARC Research Fellow in Statistics in La Trobe University, Melbourne in Sep 2016 to Jan 2018. I was a one-year postdoctoral fellow in City University of Hong Kong in Oct 2015 to Aug 2016 and a half-year research assistant in University of New South Wales, Australia in Apr 2015 to Oct 2015. I obtained my PhD in UNSW Australia under the supervision of Prof Ian Sloan, A/Prof Robert Womersley and Prof Michael Cowling.

I am interested in computational mathematics, statistical analysis, data science and machine learning, in particular in

  • Tight frames, Fast algorithms, Sparse approximation
  • Geometric Deep Learning, Distributed Learning, Optimization Algorithms, Data Theory, Information Geometry
  • Computational Astrophysics and Astrostatistics
  • Spatial Statistics and Bayesian Methods
  • Infinite-dimensional SDEs, Random fields

My Research Supervision


Areas of supervision

Computational Mathematics, Data Science, Machine Learning

I am/was a tutor for the following courses in UNSW Sydney. 

  • Semester 3 2019, MATH3101/5305 Computational Mathematics (Numerical Methods for PDEs)
  • Semester 2 2018, MATH2089 Numerical Methods and Statistics
  • Semester 1 2015, MATH1131 Mathematics 1A
  • Semester 2 2014, MATH1231 Mathematics 1B, MATH1241 Higher Mathematics 1B, MATH2019 Engineering Mathematics 2E

I have co-supervisor of two masters students in Statistics and Data Science at UNSW, 2018--2019.

  • Yi Guo, thesis title: Cosmo-Encoder: A Bayesian deep learning approach for cosmic microwave background inpainting.
  • Kai Yi, thesis title: Variational autoencoder for cosmic microwave background image inpainting. 
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Location

School of Mathematics and Statistics
UNSW Sydney
NSW 2052
The Red Centre
Room 2075

Contact

9385 7076/4239
9385 7123