RESEARCH
RESEARCH
Research Interests
Deep Learning Theory
Statistical Machine Learning
Deep Neural Networks
Functional Data Analysis
Applications of Machine Learning
Research Grants (as Principal Investigator)
External grants from Research Grants Council of Hong Kong
Generalization analysis of operator learning by deep neural networks, GRF 12303024, 2025-2027.
Approximation analysis of outcome weighted learning by convolutional neural networks, GRF 12302923, 2024-2026.
Learning theory of outcome weighted schemes and related topics, GRF 12303220, 2021-2023.
Analysis of kernel-based learning and testing schemes for large-scale data, GRF 12302819, 2020-2022.
Weighted Tubal decompositions for tensors with applications in image processing, GRF 12301619 (transferred from Weiyang Ding), 2019-2022.
Mathematical analysis of kernel based modal regression schemes, ECS 22303518, 2018-2021.
Other external grants
A study on deep learning methods for inverse scattering problems, Guangdong-Hong Kong Universities “1+1+1” Joint Funding Programme 2025A0505000007, 2025-2028.
Kernel density estimation driven supervised learning: Algorithms and theory, Guangdong Basic and Applied Basic Research Fund 2024A1515011878, 2024-2026.
Learning theory of Kaczmarz methods for phase retrieval, National Natural Science Foundation of China, Young Scientists Fund 11801478, 2019-2021.
Internal grants
Deep information theoretic learning with application to healthcare, Initiation Grant for Faculty Niche Research Areas (IG-FNRA), 2023-2025.
Optimal estimation for functional regression via spectral filtering, Faculty Research Grant (FRG), 2018-2019.
Editorial Board
Associate Editor, Frontiers in Applied Mathematics and Statistics (section Statistics and Probability), 2023-present
Editorial Board, Journal of Mathematics, 2022-present
Associate Editor, International Journal of Reproducing Kernels, 2021-present
Associate Editor, Software Impacts, 2021-present
Associate Editor, Mathematical Foundations of Computing, 2019-present