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Yu Guang Wang |
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yuguang.wang@mis.mpg.de yuguang.wang@unsw.edu.au |
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Max Planck Institute for Mathematics in the Sciences & University of New South Wales |
Max Planck Institute for Mathematics in the Sciences Inselstrasse 22, 04103 Leipzig Germany |
I am a scientist (postdoc) at Max Planck Institute for Mathematics in Sciences, hosted by Prof Guido Montúfar. I am also an adjunct associate lecturer at UNSW Sydney. 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).
• | Deep Learning Theory & Math Machine Learning Seminar, |
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• | Annual Meeting of Australian Mathematical Society (AustMS'20), |
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• | Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS'20), Virtual, 6 Dec - 12 Dec 2020. | |
• | AI Group Seminar, |
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• | IMA Workshop on Theory and Algorithms in Graph-based Learning, |
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• | GAMM AG Workshop Computational and Mathematical Methods in Data Science, |
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• | Thirty-seventh International Conference on Machine Learning (ICML'20), Virtual, 12 Jul - 18 Jul 2020. |
I am a Guest Editor for Special Issue Deep Neural Networks for Graphs: Theory, Models, Algorithms and Applications in
I am a review Editor for the journal Frontiers in Applied Mathematics and Statistics.
I am a reviewer for ICML'20 (Top Reviewer), ICML'21, NeurIPS'20, ICLR'21, IJCAI'21.
I am an organiser for Collaborate@ICERM on Geometry of Data and Networks, 2019 joint with Joan Bruna
I am an organiser for Minisymposium on Harmonic Analysis for Graph Signal Processing and Deep Learning Applications in
I was a class tutor in UNSW for following courses.
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 four PhD students:
Xuebin Zheng, |
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Bingxin Zhou, |
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Nicole Hallet, |
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. |
Copyright @ 2020 Yu Guang Wang | Top |