査読付き論文誌，会議録
1. J. C. Butcher, T. Mitsui, Y. Miyatake, S. Sato, On the B-series composition theorem, to appear in BIT
2. K. Umezu, S. Sato, T. Matsuo, A discrete variational derivative method for the Cahn--Hilliard equation with high-order spatial accuracy, to appear in JSIAM Letters
3. S. Kawai, S. Sato, T. Matsuo, Mathematical analysis and numerical comparison of energy-conservative schemes for the Zakharov equations, Japan J. Indust. Appl. Math., 42: 259-288, 2024.
4. S. Kawai, S. Sato, T. Matsuo, Mathematical analysis of a norm-conservative numerical scheme for the Ostrovsky equation, Japan J. Indust. Appl. Math., 42: 153-176, 2024.
5. N. Ishii, S. Sato, T. Matsuo, Affine-invariant projection methods for conservative integration of differential equations, JSIAM Letters, 16: 49--52, 2024.
6. K. Ushiyama, S. Sato, T. Matsuo, Properties and practicability of convergence-guaranteed optimization methods derived from weak discrete gradients, Numer. Algorithms, 96: 1331--1362, 2024.
7. S. Sato, High-order linearly implicit exponential integrators conserving quadratic invariants with application to scalar auxiliary variable approach, Numer. Algorithms, 96: 1295--1329, 2024.
8. T. Kamijima, S. Sato, K. Ushiyama, T. Matsuo, K. Tanaka, Analysis of continuous dynamical system models with Hessians derived from optimization methods, JSIAM Letters, 16: 29--32, 2024.
9. K. Onuma, S. Sato, Existence results on Lagrange multiplier approach for gradient flows and application to optimization, Japan J. Indust. Appl. Math., 41: 165--189, 2024.
10. K. Ushiyama, S. Sato, T. Matsuo, A unified discretization framework for differential equation approach with Lyapunov arguments for convex optimization, Adv. Neural Inf. Process. Syst., 36: 26092--26120, 2023.
11. S. Sato, Y. Miyatake, J. C. Butcher, High-order linearly implicit schemes conserving quadratic invariants, Appl. Numer. Math., 187: 71--88, 2023.
12. K. Ushiyama, S. Sato, T. Matsuo, Essential convergence rate of ordinary differential equations appearing in optimization, JSIAM Letters, 14: 119--122, 2022.
13. T. Kemmochi, S. Sato, Scalar auxiliary variable approach for conservative/dissipative partial differential equations with unbounded energy functionals, BIT, 62: 903--930, 2022.
14. K. Ushiyama, S. Sato, T. Matsuo, Deriving efficient optimization methods based on stable explicit numerical methods, JSIAM Letters, 14: 29--32, 2022.
15. S. Eidnes, L. Li, S. Sato, Linearly implicit structure-preserving schemes for Hamiltonian systems, J. Comput. Appl. Math., 387: 112489, 2021.
16. T. Matsuoka, S. Sato, Making bidirected graphs strongly connected, Algorithmica, 82: 787--807, 2020.
17. S. Sato, Linear gradient structures and discrete gradient methods for conservative/dissipative differential-algebraic equations
, BIT, 59(4): 1063--1091, 2019.
18. S. Sato, K. Oguma, T. Matsuo, B.-F. Feng, A robust numerical integrator for the short pulse equation near criticality
, J. Comput. Appl. Math., 361: 343--365, 2019.
19. S. Sato, T. Matsuo, On spatial discretization of evolutionary differential equations on the periodic domain with a mixed derivative, J. Comput. Appl. Math., 358: 221--240, 2019.
20. S. Sato, Stability and convergence of a conservative finite difference scheme for the modified Hunter--Saxton equation
, BIT, 59(1): 213--241, 2019.
21. Y. Sugibuchi, T. Matsuo, S. Sato, Constructing invariant-preserving numerical schemes based on Poisson and Nambu brackets
, JSIAM Letters, 10: 53--56, 2018.
22. S. Sato, Combinatorial relaxation algorithm for the entire sequence of the maximum degree of minors, Algorithmica, 77: 815--835, 2017.
23. D. Furihata, S. Sato, T. Matsuo, A novel discrete variational derivative method using ``average-difference methods'', JSIAM Letters, 8: 81--84, 2016.
24. S. Sato, T. Matsuo, H. Suzuki, D. Furihata, A Lyapunov-type theorem for dissipative numerical integrators with adaptive time-stepping, SIAM J. Numer. Anal., 53(6): 2505--2518, 2015.
25. S. Sato, Combinatorial relaxation algorithm for the entire sequence of the maximum degree of minors in mixed polynomial matrices
, JSIAM Letters, 7: 49--52, 2015.
26. S. Sato, T. Matsuo, D. Furihata, An analysis on the asymptotic behavior of multistep linearly implicit schemes for the Duffing equation, JSIAM Letters, 7: 45--48, 2015.

書籍
1. 宮武勇登, 佐藤峻, 微分方程式の数値解析とデータサイエンス, SGCライブラリ199, サイエンス社, 2025.
2. J.C.ブッチャー (著), 三井斌友 (翻訳), 宮武勇登 (翻訳), 佐藤峻 (翻訳), B級数：数値解析の代数的解析, 丸善出版, 2024.

2023年7月 日本応用数理学会 2023年度 JSIAM Letters 論文賞
2016年6月 EASIAM student paper prize, SIAM: East Asian Section Conference 2016 (1st prize)
2016年3月 東京大学大学院情報理工学系研究科長賞
2015年6月 日本応用数理学会 第11回 若手優秀講演賞
2014年3月 東京大学工学部長賞

2024年6月--現在
論文誌 日本応用数理学会論文誌 編集委員
2021年4月--現在
論文誌 JSIAM Letters 編集委員
2019年7月--2024年6月
数値解析シンポジウム 実行委員
2019年7月--2023年3月
日本応用数理学会 「若手の会」研究部会 運営委員

• 微分積分II g
• 基礎微分積分
• アルゴリズムＡ演習
• アルゴリズムＡ
• 応用数理特論1
• 先端応用数理特論1

• 組織再編前旧課程の同時開講科目等が含まれており、掲載されている全ての科目を開講するわけではありません。