Siu WunCheung

Center for Applied Scientific Computing
Email: cheung26@llnl.gov
Phone: +19254221718

Siu Wun (Tony) Cheung is a postdoctoral research scientist in the Center for Applied Scientific Computing at Lawrence Livermore National Laboratory. He obtained his doctoral degree in Mathematics from Texas A&M University in 2020, under the direction of Prof. Yalchin Efendiev. His broad research area is in computational mathematics and scientific computing. His current research interests include finite element methods, discontinuous Galerkin methods, reduced order modeling, multiscale methods and scientific machine learning.

Personal Homepage (Not affiliated with or sponsored by LLNL): https://siuwuncheung.github.io/

Selected Publications (Full publication list on Google Scholar):

  1. Siu Wun Cheung, Eric T. Chung and Wing Tat Leung.
    Constraint Energy Minimizing Generalized Multiscale Discontinuous Galerkin Method.
    Journal of Computational & Applied Mathematics 380 (2020), 112960.

  2. Siu Wun Cheung, Eric T. Chung, Yalchin Efendiev, Eduardo Gildin, Yating Wang and Jingyan Zhang.
    Deep Global Model Reduction Learning in Porous Media Flow Simulation.
    Computational Geosciences, 24 (2020), 261-274.

  3. Min Wang, Siu Wun Cheung, Wing Tat Leung, Eric T. Chung, Yalchin Efendiev and Mary Wheeler.
    Reduced-order Deep Learning for Flow Dynamics. The Interplay Between Deep Learning and Model Reduction.
    Journal of Computational Physics 401 (2020), 108939.

  4. Siu Wun Cheung and Nilabja Guha.
    Dynamic Data-driven Bayesian GMsFEM.
    Journal of Computational & Applied Mathematics 353 (2019), 72-85.

  5. Siu Wun Cheung, Eric Chung and Hyea Hyun Kim.
    A Mass Conservative Scheme for Fluid-Structure Interaction Problems by the Staggered Discontinuous Galerkin Method.
    Journal of Scientific Computing (2018) 74:1423–1456.