I am an Associate Professor in Institute of Natural Sciences, School of Mathematical Sciences, Department of Computer Science and Engineering, and AI Biomedicine Center of Zhangjiang Institute for Advanced Study, and Key Lab of Scientific and Engineering Computing of Minister of Education (MOE-LSC), at Shanghai Jiao Tong University. I am a PI of Shanghai AI Laboratory. I am also Adjunct Associate Professor at UNSW Sydney.
My research interests lie in artificial intelligence, computational mathematics, statistics and data science. In particular, I am working on geometric deep learning, graph neural networks, applied harmonic analysis, Bayesian inference, information geometry, numerical analysis, and applications to biomedicine and protein design.
Previously, I was a research scientist at Max Planck Institute for Mathematics in Sciences, in Prof Guido Montufar's Deep Learning Theory Group. I obtained my PhD in applied mathematics from University of New South Wales under supervision of Prof Ian Sloan and Rob Womersley. I am a recipient of ICERM Semester Postdoctoral Fellowship of Brown University (2018), a long-term IPAM visitor of UCLA (2019), and long-term visitor of AI Group of Prof Pietro Lio at Univeristy of Cambridge (2022).
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.
https://orcid.org/0000-0002-7450-0273