Prof SEAN Y HON
Prof SEAN Y HON
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After completing his DPhil in Mathematics at the University of Oxford, Sean is now an Assistant Professor at Hong Kong Baptist University. His research interests lie in numerical analysis, the mathematics of data science, and computational finance.
Sean's current research focuses on developing theoretical frameworks and numerical methods for evolutionary partial differential equations (PDEs), PDE-constrained optimization, option pricing, and deep learning.
He is also actively exploring diagonalization-based parallel-in-time (ParaDiag) preconditioners and preconditioning techniques for Toeplitz-related systems, which arise in a broad range of applications. ParaDiag methods aim to enhance the efficiency of time-parallel solvers for evolutionary PDE problems.
As for Toeplitz-related systems, these are ubiquitous in mathematics and physics—they appear in numerical PDEs, approximation theory, compressed sensing, image processing, and more. Efficient preconditioning is crucial to accelerate the solution of linear systems involving Toeplitz structures, making this an important area of research.
EDUCATION
EDUCATION
Doctor of Philosophy in Mathematics, University of Oxford, 2018
Master of Philosophy in Mathematics, Hong Kong University of Science and Technology, 2014
Bachelor of Science in Mathematics, Hong Kong University of Science and Technology, 2012
AWARDS AND HONOURS (SELECTED)
AWARDS AND HONOURS (SELECTED)
Research Excellence Paper Award, Hong Kong Baptist University, 2023
Early Career Award, Hong Kong University Grants Committee, 2021
The 7th BGCE Best Student Prize (Finalist), SIAM Conference on Computational Science and Engineering, 2019
University of Oxford Croucher Scholarship, Croucher Foundation and University of Oxford, 2014
EXPERTISE AND SPECIALISATIONS
EXPERTISE AND SPECIALISATIONS
Fast iterative solvers for partial differential equations (PDEs)
Diagonalization-based parallel-in-time (ParaDiag) preconditioning for evolutionary PDE problems
Numerical fractional PDEs
Fast iterative solvers for optimal control of PDEs
Preconditioning for Toeplitz-related systems
Approximation theory in scientific machine learning
RESEARCH TEAM (Current)
RESEARCH TEAM (Current)
Jiamei Dong (PhD Candidate, 2021 - Now)
Congcong Li (PhD Candidate, 2022 - Now)
Wai Yan (MPhil Candidate, 2022 - Now)
Yuanyuan Huang (Research Associate, Nov 2023 - Now)
Past: PhD at University of Macau
RESEARCH TEAM (Past)
RESEARCH TEAM (Past)
PhD under my supervision:
Rosita L. Sormani (co-supervised with Stefano Serra-Capizzano, 2021 - 2025)
Past: PhD at University of Insubria
Current: Postdoc at University of Cagliari
Research Associate:
Grigorios Tachyridis (Apr 2024 - Sep 2024)
Past: PhD at University of Ioannina
Current: Adjunct Professor at Athens University of Economics and Business
Research Assistant:
Po Yin Fung (Jan 2023 - May 2025)
Past: BSc in Mathematics at Hong Kong University of Science and Technology
Current: MSc in Applied and Computational Mathematics at Simon Fraser University
Qunhui Guo (Feb 2023 - Aug 2023)
Past: MSc in Mathematics at National University of Singapore
Current: PhD Candidate in Industrial Engineering at Northeastern University
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