Rchr
J-GLOBAL ID：201901019754686837   Update date: Oct. 21, 2024

Sato Shun

サトウ シュン | Sato Shun
Homepage URL  (2)： https://shun-310.github.io/ja/ ,  https://shun-310.github.io/
Research field  (1)： Applied mathematics and statistics
Research keywords  (4)： Geometric Numerical Integration ,  Evolutionary Differential Equations ,  Numerical Analysis ,  連続最適化
Research theme for competitive and other funds  (6)：
  • 2024 - 2028 Analysis and creation of numerical analysis algorithms using product-type neural network deep learning
  • 2024 - 2027 Exploring the best dynamical systems for optimization and deep learning
  • 2022 - 2027 微分代数方程式に対する高速な構造保存数値解法の構築
  • 2020 - 2024 Creation of a foundation for a numerical approach to deep learning
  • 2019 - 2022 微分代数方程式に対する構造保存数値解法の理論構築と発展方程式への応用
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Papers (25)：
  • Shuto Kawai, Shun Sato, Takayasu Matsuo. Mathematical analysis and numerical comparison of energy-conservative schemes for the Zakharov equations. Japan Journal of Industrial and Applied Mathematics. 2024
  • Shuto Kawai, Shun Sato, Takayasu Matsuo. Mathematical analysis of a norm-conservative numerical scheme for the Ostrovsky equation. Japan Journal of Industrial and Applied Mathematics. 2024
  • Naoki Ishii, Shun Sato, Takayasu Matsuo. Affine-invariant projection methods for conservative integration of differential equations. JSIAM Letters. 2024. 16. 49-52
  • Tomoya Kamijima, Shun Sato, Kansei Ushiyama, Takayasu Matsuo, Ken’ichiro Tanaka. Analysis of continuous dynamical system models with Hessians derived from optimization methods. JSIAM Letters. 2024. 16. 29-32
  • Kansei Ushiyama, Shun Sato, Takayasu Matsuo. Properties and practicability of convergence-guaranteed optimization methods derived from weak discrete gradients. Numerical Algorithms. 2024. 96. 3. 1331-1362
ｍore...
Books (1)：
  • B級数 : 数値解法の代数的解析
    丸善出版 2024 ISBN:9784621309056
Lectures and oral presentations  (37)：
  • Linearly implicit conservative exponential integrators for scalar auxiliary variable approach
    (Workshop on Numerical Methods and Analysis for PDEs 2024)
  • Convergence rates of optimization methods in continuous and discrete time
    (International Conference on Scientific Computing and Machine Learning 2024 2024)
  • 連続最適化問題に対する常微分方程式によるアプローチ
    (セミナーシリーズ「物理学・応用数学の数値計算最前線」 2024)
  • 連続最適化手法とその連続極限における収束レートの対応について
    (RIMS共同研究(公開型)「新時代における高性能科学技術計算法の探究」 2023)
  • 連続最適化への応用に向けた常微分方程式の数値解析入門
    (連続最適化および関連分野に関する夏季学校 2023 2023)
ｍore...
Education (3)：
  • 2016 - 2019 The University of Tokyo The Graduate School of Information Science and Technology Department of Mathematical Informatics
  • 2014 - 2016 The University of Tokyo The Graduate School of Information Science and Technology Department of Mathematical Informatics
  • 2011 - 2014 The University of Tokyo The Faculty of Engineering Department of Mathematical Engineering and Information Physics
Professional career (1)：
  • PhD (The University of Tokyo)
Work history (2)：
  • 2019/04 - 現在 The University of Tokyo Assistant professor
  • 2016/04 - 2019/03 JSPS JSPS Research Fellowship for Young Scientists, DC1
Committee career (3)：
  • 2021/04 - 現在 論文誌 JSIAM Letters 編集委員
  • 2019/07 - 2024/06 数値解析シンポジウム 実行委員
  • 2019/07 - 2023/03 日本応用数理学会 「若手の会」研究部会 運営委員
Awards (5)：
  • 2023/07 - JSIAM Letters 論文賞 Essential convergence rate of ordinary differential equations appearing in optimization
  • 2016/06 - EASIAM EASIAM student paper prize (1st prize)
  • 2016/03 - The University of Tokyo Dean's award from Graduate School of Information Science and Technology
  • 2015/06 - Japan Society for Industrial and Applied Mathematics Best Presentation Award
  • 2014/03 - The University of Tokyo Dean's award from Faculty of Engineering
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