Dr Yu Guang Wang | UNSW Research

Fields of Research (FoR)

Applied Mathematics, Numerical and Computational Mathematics, Statistics, Knowledge Representation and Machine Learning, Computer Graphics, Pattern Recognition and Data Mining

SEO tags

Expanding Knowledge

Biography

I am an adjunct associate lecturer at UNSW Sydney. I am also a scientist at Max Planck Institute for Mathematics in Sciences, in Mathematics Machine Learning group, hosted by Prof Guido Montúfar. My research interests lie in computational mathematics, statistics, machine learning, and data science. In particular, I am working on deep learning, graph neural networks, applied harmonic analysis, Bayesian inference, information geometry, random fields, numerical analysis, and applications to healthcare, biomedical technology and cosmology. I obtained my PhD in applied mathematics from University of New South Wales under supervision of Prof Ian Sloan and Rob Womersley. I have been a semester-long visitor of IPAM, UCLA (2019) and ICERM, Brown University (2018).

My Research Supervision

Areas of supervision

Applied 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 am supervising three PhD students:

Kai Yi, UNSW Statistics and Data Science, research on deep Bayesian learning, graph neural networks, since 2019 (chief supervisor, joint with A/Prof Yanan Fan, Dr Jan Hamann)
Xuebin Zheng, University of Sydney Business Analytics, research on graph neural networks, since 2018 (co-supervisor, with Prof Junbin Gao)
Binxing Zhou, University of Sydney Business Analytics, research on graph neural networks, manifold learning, since 2018 (co-supervisor, with Prof Junbin Gao).

I have co-supervised 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.

View less