Myself

Left: Me; Right: Gilbert Strang; At SIAM AN18, Portland OR

 

 

 

Current Teaching Activities
About Me

 

Simon is an ordinary person born and raised in Macau (the former and the last colony of Portugal). He is a first-generation college student in his family. He traveled to Beijing in 2011 and started studying mathematics since then. In 2015, he came to Hong Kong to continue his journey of PhD in mathematics. His career started in College Station TX. He aims at understanding the real and yet complex world, on which he desires to make an impact, through his mathematical knowledge and expertise. Currently, he focuses on Financial Modeling using Machine Learning from a more practical and realistic perspective. As a quantiative researcher, he tries to leverage right amount of science to make considerable revenue.
Academic Publications

 

Since 2017, Simon has published 21 research papers in different journals (including arXiv). He would like to thank all of his advisors and collaborators with whom he worked for their guidance and help.
  1. E. Chung, S. Pollock and S.-M. Pun. Goal-oriented adaptivity of mixed GMsFEM for flows in heterogeneous media. Computer Methods in Applied Mechanics and Engineering, 323 (2017), pp.151-173.
  2. E. Chung, S.-M. Pun and Z. Zhang. An adaptive dynamically low-dimensional approximation method for multiscale stochastic diffusion equations. Journal of Computational and Applied Mathematics, 393 (2019), pp.302-313.
  3. R. Altmann, E. Chung, R. Maier, D. Peterseim and S.-M. Pun. Computational multiscale methods for linear heterogeneous poroelasticity. Journal of Computational Mathematics 38 (1) 2020, 41-57.
  4. E. Chung, S. Pollock and S.-M. Pun. Online basis construction for goal-oriented adaptivity in the GMsFEM. Journal of Computational Physics, 393 (2019), pp.59-73.
  5. S. Fu, R. Altmann, E. Chung, R. Maier, D. Peterseim and S.-M. Pun. Computational multiscale methods for linear heterogeneous poroelasticity with high contrast. Journal of Computational Physics, 395 (2019), pp.286-297.
  6. E. Chung and S.-M. Pun. Online adaptive basis enrichment for mixed CEM-GMsFEM. Multiscale Modeling & Simulation 17 (4) 2019, 1103-1122.
  7. E. Chung and S.-M. Pun. Computational multiscale methods for first-order wave equation using CEM-GMsFEM. Journal of Computational Physics 409, 109359, 2020.
  8. E. Chung, J. Hu, and S.-M. Pun. Convergence of the CEM-GMsFEM for Stokes flows in heterogeneous perforated domains. Journal of Computational and Applied Mathematics (2021), 113327.
  9. E. Chung, W.-T. Leung, S.-M. Pun, and Z.-C. Zhang. A multi-stage deep learning based algorithm for multiscale model reduction. Journal of Computational and Applied Mathematics (2021), 113506.
  10. B. Chetverushkin, E. Chung, Y. Efendiev, S.-M. Pun, and Z.-C. Zhang. Computational multiscale methods for quasi-gas dynamic equations. Journal of Computational Physics (2021), 110352.
  11. Y. Efendiev, S.-M. Pun, and and P. N. Vabishchevich. Temporal splitting algorithms for non-stationary multiscale problems. Journal of Computational Physics (2021), 110375.
  12. S. W. Cheung, E. Chung, Y. Efendiev, W.-T. Leung, and S.-M. Pun. Iterative Oversampling Technique for Constraint Energy Minimizing Generalized Multiscale Finite Element Method in the Mixed Formulation. Applied Mathematics and Computation 415, 126622, 2021.
  13. X. Su and S.-M. Pun. A multiscale method for the heterogeneous Signorini Problem. Journal of Computational and Applied Mathematics (2022), 114160.
  14. E. Chung, Y. Efendiev, S.-M. Pun, and Z.-C. Zhang. Computational multiscale methods for parabolic wave approximations in heterogeneous media. Applied Mathematics and Computation 425, 127044, 2022.
  15. Y. Efendiev, W.-T. Leung, W. Li, S.-M. Pun, and P. N. Vabishchevich. Nonlocal transport equations in multiscale media. Modeling, dememorization, and discretizations. Journal of Computational Physics 472, 111555, 2023.
  16. X. Su and S.-M. Pun. Fast online adaptive enrichment for poroelasticity with high contrast. Journal of Computational Physics 487, 112171, 2023.
  17. S.-M. Pun and S. W. Cheung. Online Adaptive Algorithm for Constraint Energy Minimizing Generalized Multiscale Discontinuous Galerkin Method. Multiscale Modeling & Simulation 21 (1) 2023, 168-193.
  18. E. Chung, W.-T. Leung, S.-M. Pun, and Z.-C. Zhang. Multi-agent Reinforcement Learning Aided Sampling Algorithms for a Class of Multiscale Inverse Problems. Journal of Scientific Computing 96.2 (2023): 55.
  19. J. Wu, S.-M. Pun, X. Zheng, and G. Chen. Construct Exchange-Correlation Functionals via Machine Learning. Journal of Chemical Physics 159, 090901 (2023).
  20. J. Hu, W.-T. Leung, E. Chung, Y. Efendiev, and S.-M. Pun. Space-time non-local multi-continua upscaling for parabolic equations with moving channelized media. arXiv preprint arXiv.2106.12010, 2021.
  21. X. Su, W. T. Leung, W. Li, and S.-M. Pun. Partially Explicit Generalized Multiscale Method for Poroelasticity Problem. arXiv preprint arXiv.2310.14199, 2023.

Past Teaching
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