Dr Yu Guang Wang

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I am an Associate Professor in ,��,��, and ��Ǵ��, and , at Shanghai Jiao Tong University. I am a PI of . I am also Adjunct Associate Professor at .

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 . I obtained my PhD in applied mathematics from University of New South Wales under supervision of Prof ��Ի��. I am a recipient of of Brown University (2018), a long-term of UCLA (2019), and long-term visitor of at Univeristy of Cambridge (2022).

Phone

+61 4 0129 7906

E-mail

yuguang.wang@unsw.edu.au

Location

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

Book Chapters | 2022

Hallett N; Hodge C; You JJ; Wang YG; Sutton G, 2022, 'Artificial Intelligence in the Diagnosis and Management of Keratoconus', in Keratoconus: Diagnosis and Treatment, pp. 275 - 289,

Book Chapters | 2018

Wang YG; Zhu H, 2018, 'Analysis of framelet transforms on a simplex', in Contemporary Computational Mathematics - A Celebration of the 80th Birthday of Ian Sloan, Springer Nature, pp. 1175 - 1189,
Journal articles | 2024

Chen H; Wang YG; Xiong H, 2024, 'Corrigendum to “Lower and upper bounds for numbers of linear regions of graph convolutional networks” [Neural Networks Volume 168, November 2023, Pages 394–404](S0893608023005191)(10.1016/j.neunet.2023.09.025)', Neural Networks, 171, pp. 144,

Journal articles | 2024

Gao R; Yuan X; Ma Y; Wei T; Johnston L; Shao Y; Lv W; Zhu T; Zhang Y; Zheng J; Chen G; Sun J; Wang YG; Yu Z, 2024, 'Harnessing TME depicted by histological images to improve cancer prognosis through a deep learning system', Cell Reports Medicine, 5,

Journal articles | 2024

Jiang Y; Shen Y; Wang Y; Ding Q, 2024, 'Automatic recognition of white blood cell images with memory efficient superpixel metric GNN: SMGNN', Mathematical Biosciences and Engineering, 21, pp. 2163 - 2188,

Journal articles | 2024

Yi K; Fan Y; Hamann J; Liò P; Wang YG, 2024, 'ABCMB: deep delensing assisted likelihood-free inference from CMB polarization maps', Machine Learning: Science and Technology, 5,

Journal articles | 2024

Zhou B; Li R; Zheng X; Wang YG; Gao J, 2024, 'Graph Denoising With Framelet Regularizers', IEEE Transactions on Pattern Analysis and Machine Intelligence, 46, pp. 7606 - 7617,

Journal articles | 2023

Chen H; Wang YG; Xiong H, 2023, 'Lower and upper bounds for numbers of linear regions of graph convolutional networks', Neural Networks, 168, pp. 394 - 404,

Journal articles | 2023

Jiang Y; Ding Q; Wang YG; Liò P; Zhang X, 2023, 'VISION GRAPH U-NET: GEOMETRIC LEARNING ENHANCED ENCODER FOR MEDICAL IMAGE SEGMENTATION AND RESTORATION', Inverse Problems and Imaging, 2023,

Journal articles | 2023

Li M; Kang L; Xiong Y; Wang YG; Fan G; Tan P; Hong L, 2023, 'SESNet: sequence-structure feature-integrated deep learning method for data-efficient protein engineering', Journal of Cheminformatics, 15,

Journal articles | 2023

Liu Y; Pan S; Wang YG; Xiong F; Wang L; Chen Q; Lee VCS, 2023, 'Anomaly Detection in Dynamic Graphs via Transformer', IEEE Transactions on Knowledge and Data Engineering, 35, pp. 12081 - 12094,

Journal articles | 2023

Wang YG; Womersley RS; Wu HT; Yu WH, 2023, 'Numerical computation of triangular complex spherical designs with small mesh ratio', Journal of Computational and Applied Mathematics, 421,

Journal articles | 2023

Zheng X; Zhou B; Li M; Wang YG; Gao J, 2023, 'MATHNET: Haar-like wavelet multiresolution analysis for graph representation learning', Knowledge-Based Systems, 273,

Journal articles | 2022

Montúfar G; Wang YG, 2022, 'Distributed Learning via Filtered Hyperinterpolation on Manifolds', Foundations of Computational Mathematics, 22, pp. 1219 - 1271,

Journal articles | 2022

Wang Y; Wang YG; Hu C; Li M; Fan Y; Otter N; Sam I; Gou H; Hu Y; Kwok T; Zalcberg J; Boussioutas A; Daly RJ; Montúfar G; Liò P; Xu D; Webb GI; Song J, 2022, 'Cell graph neural networks enable the precise prediction of patient survival in gastric cancer', npj Precision Oncology, 6,

Journal articles | 2022

Zheng X; Zhou B; Wang YG; Zhuang X, 2022, 'Decimated Framelet System on Graphs and Fast G-Framelet Transforms', Journal of Machine Learning Research, 23

Journal articles | 2022

Zhou B; Zheng X; Wang YG; Li M; Gao J, 2022, 'Embedding graphs on Grassmann manifold', Neural Networks, 152, pp. 322 - 331,

Journal articles | 2021

Anh VV; Olenko A; Wang YG, 2021, 'Fractional stochastic partial differential equation for random tangent fields on the sphere', Theory of Probability and Mathematical Statistics, 104, pp. 3 - 22,

Journal articles | 2021

Bodnar C; Frasca F; Wang YG; Otter N; Montúfar G; Liò P; Bronstein M, 2021, 'Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks',

Journal articles | 2021

Hamann J; Le Gia QT; Sloan IH; Wang YG; Womersley RS, 2021, 'A new probe of Gaussianity and isotropy with application to cosmic microwave background maps', International Journal of Modern Physics C, 32,

Journal articles | 2021

Le Gia QT; Li M; Wang YG, 2021, 'Algorithm 1018: FaVeST-Fast Vector Spherical Harmonic Transforms', ACM Transactions on Mathematical Software, 47,

Journal articles | 2021

Ma Z; Xuan J; Wang YG; Li M; LiÃ² P, 2021, 'Path integral based convolution and pooling for graph neural networksThis article is an updated version of: Ma Z, Xuan J, Wang Y G, Li M and LiÃ² P 2020 Path integral based convolution and pooling for graph neural networks Advances in Neural Information Processing Systems vol 33 ed H Larochelle, M Ranzato, R Hadsell, M F Balcan and H Lin (New York: Curran Associates) pp 16421–33.', Journal of Statistical Mechanics: Theory and Experiment, 2021,

Journal articles | 2021

Sourisseau M; Wang YG; Womersley RS; Wu HT; Yu WH, 2021, 'Improve concentration of frequency and time (ConceFT) by novel complex spherical designs', Applied and Computational Harmonic Analysis, 54, pp. 137 - 144,

Journal articles | 2021

Zheng X; Zhou B; Gao J; Wang YG; Lio P; Li M; Montufar G, 2021, 'How Framelets Enhance Graph Neural Networks',

Journal articles | 2020

Hallett N; Yi K; Dick J; Hodge C; Sutton G; Guang Wang Y; You J, 2020, 'Deep Learning Based Unsupervised and Semi-supervised Classification for Keratoconus', Proceedings of the International Joint Conference on Neural Networks,

Journal articles | 2020

Li M; Ma Z; Wang YG; Zhuang X, 2020, 'Fast Haar Transforms for Graph Neural Networks', Neural Networks, 128, pp. 188 - 198,

Journal articles | 2020

Lin SB; Wang YG; Zhou DX, 2020, 'Distributed filtered hyperinterpolation for noisy data on the sphere', SIAM Journal on Numerical Analysis, 59, pp. 634 - 659,

Journal articles | 2020

Ma Z; Xuan J; Wang YG; Li M; Liò P, 2020, 'Path integral based convolution and pooling for graph neural networks', Advances in Neural Information Processing Systems, 2020-December

Journal articles | 2020

Sourisseau M; Wang YG; Womersley RS; Wu H-T; Yu W-H, 2020, 'Improve Concentration of Frequency and Time (Conceft) by Novel Complex Spherical Designs', ,

Journal articles | 2020

Wang YG; Li M; Zheng M; Montufar G; Zhang X; Fan Y, 2020, 'Haar Graph Pooling', Proceedings of international conference on machine learning (ICML), 119, pp. 9952 - 9962,

Journal articles | 2020

Wang YG; Zhuang X, 2020, 'Tight framelets and fast framelet filter bank transforms on manifolds', Applied and Computational Harmonic Analysis, 48, pp. 64 - 95,

Journal articles | 2020

Yi K; Guo Y; Fan Y; Hamann J; Wang YG, 2020, 'Cosmo VAE: Variational Autoencoder for CMB Image Inpainting', Proceedings of the International Joint Conference on Neural Networks,

Journal articles | 2020

Yi K; Guo Y; Hamann J; Fan Y; Wang Y, 2020, 'CosmoVAE: Variational Autoencoder for CMB Image Inpainting', IEEE Proceedings of the International Joint Conference on Neural Networks (IJCNN)

Journal articles | 2020

Zheng X; Zhou B; Wang YG; Zhuang X, 2020, 'Decimated Framelet System on Graphs and Fast G-Framelet Transforms', ,

Journal articles | 2019

Gia QTL; Li M; Wang YG, 2019, 'FaVeST: Fast Vector Spherical Harmonic Transforms', ,

Journal articles | 2019

Gia QTL; Sloan IH; Womersley RS; Wang YG, 2019, 'Isotropic sparse regularization for spherical harmonic representations of random fields on the sphere', Applied and Computational Harmonic Analysis,

Journal articles | 2019

Li M; Broadbridge P; Olenko A; Wang YG, 2019, 'Fast Tensor Needlet Transforms for Tangent Vector Fields on the Sphere', ,

Journal articles | 2019

Ma Z; Li M; Wang Y, 2019, 'PAN: Path Integral Based Convolution for Deep Graph Neural Networks', ICML 2019 Workshop on Learning and Reasoning with Graph-Structured Representations (Oral),

Journal articles | 2019

Wang YG; Womersley RS; Wu H-T; Yu W-H, 2019, 'Numerical computation of triangular complex spherical designs with small mesh ratio',

Journal articles | 2018

Anh VV; Broadbridge P; Olenko A; Wang YG, 2018, 'On approximation for fractional stochastic partial differential equations on the sphere', Stochastic Environmental Research and Risk Assessment, 32, pp. 2585 - 2603,

Journal articles | 2018

Brauchart JS; Reznikov AB; Saff EB; Sloan IH; Wang YG; Womersley RS, 2018, 'Random Point Sets on the Sphere-Hole Radii, Covering, and Separation', EXPERIMENTAL MATHEMATICS, 27, pp. 62 - 81,

Journal articles | 2018

Brauchart JS; Reznikov AB; Saff EB; Sloan IH; Wang YG; Womersley RS, 2018, 'Random Point Sets on the Sphere—Hole Radii, Covering, and Separation', Experimental Mathematics, 27, pp. 62 - 81,

Journal articles | 2018

Brauchart JS; Reznikov AB; Saff EB; Sloan IH; Wang YG; Womersley RS, 2018, 'Random Point Sets on the Sphere—Hole Radii, Covering, and Separation', Experimental Mathematics, 27, pp. 62 - 81,

Journal articles | 2018

Brauchart JS; Reznikov AB; Saff EB; Sloan IH; Wang YG; Womersley RS, 2018, 'Random Point Sets on the Sphere—Hole Radii, Covering, and Separation', Experimental Mathematics, 27, pp. 62 - 81,

Journal articles | 2017

Le Gia QT; Sloan IH; Wang YG; Womersley RS, 2017, 'Needlet approximation for isotropic random fields on the sphere', Journal of Approximation Theory, 216, pp. 86 - 116,

Journal articles | 2017

Wang YG; Le Gia QT; Sloan IH; Womersley RS, 2017, 'Fully discrete needlet approximation on the sphere', Applied and Computational Harmonic Analysis, 43, pp. 292 - 316,

Journal articles | 2016

Brauchart JS; Reznikov AB; Saff EB; Sloan IH; Wang YG; Womersley RS, 2016, 'Random Point Sets on the Sphere—Hole Radii, Covering, and Separation', Experimental Mathematics, pp. 1 - 20,

Journal articles | 2016

Cao F; Wang D; Zhu H; Wang Y, 2016, 'An iterative learning algorithm for feedforward neural networks with random weights', Information Sciences, 328, pp. 546 - 557,

Journal articles | 2016

Wang Y, 2016, 'Filtered polynomial approximation on the sphere', Bulletin of the Australian Mathematical Society, 93, pp. 162 - 163,

Journal articles | 2016

Wang YG; Sloan IH; Womersley RS, 2016, 'Riemann Localisation on the Sphere', Journal of Fourier Analysis and Applications, 24, pp. 1 - 43,

Journal articles | 2015

Brauchart JS; Dick J; Saff EB; Sloan IH; Wang YG; Womersley RS, 2015, 'Covering of spheres by spherical caps and worst-case error for equal weight cubature in Sobolev spaces', Journal of Mathematical Analysis and Applications, 431, pp. 782 - 811,

Journal articles | 2015

Brauchart JS; Reznikov AB; Saff EB; Sloan IH; Wang YG; Womersley RS, 2015, 'Random Point Sets on the Sphere --- Hole Radii, Covering, and Separation',

Journal articles | 2014

Wang Y; Cao F, 2014, 'Approximation by semigroup of spherical operators', Frontiers of Mathematics in China, 9, pp. 387 - 416,

Journal articles | 2013

Chen ZX; Zhu HY; Wang YG, 2013, 'A modified extreme learning machine with sigmoidal activation functions', Neural Computing and Applications, 22, pp. 541 - 550,

Journal articles | 2011

Wang Y; Cao F; Yuan Y, 2011, 'A study on effectiveness of extreme learning machine', Neurocomputing, 74, pp. 2483 - 2490,

Journal articles | 2011

Wang Y; Cao F, 2011, 'Approximation by Boolean sums of Jackson operators on the sphere', Journal of Computational Analysis and Applications, 13, pp. 830 - 842

Journal articles | 2011

Yuan Y; Wang Y; Cao F, 2011, 'Optimization approximation solution for regression problem based on extreme learning machine', Neurocomputing, 74, pp. 2475 - 2482,

Journal articles | 2009

Cao F; Wang Y, 2009, 'The direct and converse inequalities for jackson-type operators on spherical cap', Journal of Inequalities and Applications, 2009, pp. 205298,
Working Papers | 2022

Yi K; Chen J; Zhou B; Lio P; Fan Y; Hamann J, 2022, Approximate Equivariance SO(3) Needlet Convolution, ,

Working Papers | 2020

Wang YG; Li M; Ma Z; Montufar G; Zhuang X; Fan Y, 2020, Haar graph pooling,

Working Papers | 2019

Hamann J; Gia QTL; Sloan IH; Wang YG; Womersley RS, 2019, A New Probe of Gaussianity and Isotropy applied to the CMB Maps, ,
Conference Papers | 2025

Liu Y; Chen Z; Wang YG; Shen Y, 2025, 'AutoProteinEngine: A Large Language Model Driven Agent Framework for Multimodal AutoML in Protein Engineering', in Proceedings - International Conference on Computational Linguistics, COLING, pp. 422 - 430

Conference Papers | 2024

Chen Z; Liu Y; Wang YG; Shen Y, 2024, 'Validation of an LLM-based Multi-Agent Framework for Protein Engineering in Dry Lab and Wet Lab', in Proceedings - 2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024, pp. 5364 - 5370,

Conference Papers | 2024

Huang K; Wang YG; Li M; Liò P, 2024, 'How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing', in Proceedings of Machine Learning Research, PMLR, Vienna, Austria, pp. 20310 - 20330, presented at 41st International Conference on Machine Learning, Vienna, Austria, 21 July 2024,

Conference Papers | 2024

Liu Y; Chen Z; Wang YG; Shen Y, 2024, 'TourSynbio-Search: A Large Language Model Driven Agent Framework for Unified Search Method for Protein Engineering', in Proceedings - 2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024, pp. 5395 - 5400,

Preprints | 2024

Shen Y; Chen Z; Mamalakis M; He L; Xia H; Li T; Su Y; He J; Wang YG, 2024, A Fine-tuning Dataset and Benchmark for Large Language Models for Protein Understanding, ,

Conference Papers | 2024

Wu T; Wang YG; Shen Y, 2024, 'LaGDif: Latent Graph Diffusion Model for Efficient Protein Inverse Folding with Self-Ensemble', in Proceedings - 2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024, pp. 3850 - 3855,

Conference Papers | 2024

Yu X; Yi K; Wang YG; Shen Y, 2024, 'A Regressor-Guided Graph Diffusion Model for Predicting Enzyme Mutations to Enhance Turnover Number', in Proceedings - 2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024, pp. 3943 - 3948,

Preprints | 2024

Zhou Y; Ge Y; Dong X; Wang Y, 2024, How Out-of-Distribution Detection Learning Theory Enhances Transformer: Learnability and Reliability,

Conference Papers | 2023

Ke X; Zhu H; Yi K; He G; Yang G; Wang YG, 2023, 'Adaptive Importance Sampling and Quasi-Monte Carlo Methods for 6G URLLC Systems', in IEEE International Conference on Communications, pp. 5272 - 5278,

Conference Papers | 2023

Li M; Sonoda S; Cao F; Wang YG; Liang J, 2023, 'How Powerful are Shallow Neural Networks with Bandlimited Random Weights?', in Proceedings of Machine Learning Research, Honolulu, Hawaii, pp. 19360 - 19384, presented at 40th International Conference on Machine Learning (ICML 2023), Honolulu, Hawaii, 23 July 2023,

Preprints | 2023

Liu X; Zhou B; Zhang C; Wang YG, 2023, Framelet Message Passing, ,

Conference Papers | 2023

Shen Y; Zhou B; Xiong X; Gao R; Wang YG, 2023, 'How GNNs Facilitate CNNs in Mining Geometric Information from Large-Scale Medical Images', in Proceedings - 2023 2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023, pp. 2227 - 2230,

Conference Papers | 2023

Wang Y; Yi K; Liu X; Wang YG; Jin S, 2023, 'ACMP: ALLEN-CAHN MESSAGE PASSING WITH ATTRACTIVE AND REPULSIVE FORCES FOR GRAPH NEURAL NETWORKS', in 11th International Conference on Learning Representations, ICLR 2023

Conference Papers | 2023

Xu C; Tan RT; Tan Y; Chen S; Wang YG; Wang X; Wang Y, 2023, 'EqMotion: Equivariant Multi-agent Motion Prediction with Invariant Interaction Reasoning', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 1410 - 1420,

Conference Papers | 2023

Yi K; Zhou B; Shen Y; Liò P; Wang YG, 2023, 'Graph Denoising Diffusion for Inverse Protein Folding', in Advances in Neural Information Processing Systems

Preprints | 2023

Yi K; Zhou B; Shen Y; Liò P; Wang YG, 2023, Graph Denoising Diffusion for Inverse Protein Folding, ,

Conference Papers | 2023

Zhou B; Jiang Y; Wang Y; Liang J; Gao J; Pan S; Zhang X, 2023, 'Robust Graph Representation Learning for Local Corruption Recovery', in ACM Web Conference 2023 - Proceedings of the World Wide Web Conference, WWW 2023, pp. 438 - 448,

Conference Papers | 2022

Banerjee PK; Karhadkar K; Wang YG; Alon U; Montufar G, 2022, 'Oversquashing in GNNs through the lens of information contraction and graph expansion', in 2022 58th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2022,

Preprints | 2022

Chen H; Wang YG; Xiong H, 2022, Lower and Upper Bounds for Numbers of Linear Regions of Graph Convolutional Networks, ,

Preprints | 2022

Shen Y; Zhou B; Xiong X; Gao R; Wang YG, 2022, How GNNs Facilitate CNNs in Mining Geometric Information from Large-Scale Medical Images, ,

Preprints | 2022

Wang Y; Yi K; Liu X; Wang YG; Jin S, 2022, ACMP: Allen-Cahn Message Passing for Graph Neural Networks with Particle Phase Transition, ,

Preprints | 2022

Zhou B; Jiang Y; Wang YG; Liang J; Gao J; Pan S; Zhang X, 2022, Robust Graph Representation Learning for Local Corruption Recovery, ,

Conference Papers | 2022

Zhou B; Liu X; Liu Y; Huang Y; Liò P; Wang YG, 2022, 'Well-conditioned Spectral Transforms for Dynamic Graph Representation', in Proceedings of Machine Learning Research

Conference Papers | 2021

Bodnar C; Frasca F; Otter N; Wang YG; Liò P; Montúfar G; Bronstein M, 2021, 'Weisfeiler and Lehman Go Cellular: CW Networks', in Advances in Neural Information Processing Systems, pp. 2625 - 2640

Conference Papers | 2021

Bodnar C; Frasca F; Wang YG; Otter N; Montúfar G; Liò P; Bronstein MM, 2021, 'Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks', in Proceedings of Machine Learning Research, pp. 1026 - 1037

Conference Papers | 2021

Zheng X; Zhou B; Gao J; Wang YG; Liò P; Li M; Montúfar G, 2021, 'How Framelets Enhance Graph Neural Networks', in Proceedings of Machine Learning Research, pp. 12761 - 12771

Preprints | 2021

Zhou B; Li R; Zheng X; Wang YG; Gao J, 2021, Graph Denoising with Framelet Regularizer, ,

Preprints | 2021

Zhou B; Liu X; Liu Y; Huang Y; Liò P; Wang Y, 2021, Spectral Transform Forms Scalable Transformer, ,

Conference Papers | 2019

Wang YG; Zhuang X, 2019, 'Tight framelets on graphs for multiscale data analysis', in Proceedings of SPIE - The International Society for Optical Engineering,

Preprints | 2017

Anh VV; Broadbridge P; Olenko A; Wang YG, 2017, On Approximation for Fractional Stochastic Partial Differential Equations on the Sphere,

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