Tokuda Satoru

トクダサトル | Tokuda Satoru

Affiliation and department：
Job title： Associate Professor

Research keywords (4)： data science , Bayesian inference , mathematical modelling , statistical mechanics

Research theme for competitive and other funds (8)：

2023 - 2027 Innovation in a guiding principle for modeling based on observed data
2020 - 2025 Operator theoretic data analysis of complicated dynamics and its itegerated utilization with mathematical models
2020 - 2024 Theory and Practice of Statistical Inference with Conditionally Independent Observations
2018 - 2024 Development of new hybrid topological materials by nano-spin ARPES
2022 - 2023 Bayesian modelling of relaxation phenomena in photomechanical crystals

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Papers (14)：

Akihiko Hirata, Satoru Tokuda, Chihiro Nakajima, Siyuan Zha. Local structural modelling and local pair distribution function analysis for Zr-Pt metallic glass. Scientific Reports. 2024. 14. 1
Kenta Goto, Kyoka Nakanishi, Fumito Tani, Satoru Tokuda. Chemical reaction in a liquid-liquid phase-separated multiple droplet: Synchronization of color change dynamics with droplet movement. Droplet. 2024. 3. 1. e93
Keisuke Hamada, Toshioh Fujibuchi, Hiroyuki Arakawa, Yuichi Yokoyama, Naoki Yoshida, Hiroki Ohura, Naonobu Kunitake, Muneyuki Masuda, Takeo Honda, Satoru Tokuda, et al. A novel approach to predict acute radiation dermatitis in patients with head and neck cancer using a model based on Bayesian probability. Physica Medica. 2023. 116. 103181
T Nishizawa, S Tokuda, T Kobayashi, K Tanaka, H Funaba, I Yamada, Y Takemura, T Tokuzawa, R Yasuhara, H Uehara, et al. Estimation of plasma parameter profiles and their derivatives from linear observations by using Gaussian processes. Plasma Physics and Controlled Fusion. 2023. 65. 12. 125006
Natsuhiko Yoshinaga, Satoru Tokuda. Bayesian modeling of pattern formation from one snapshot of pattern. Physical Review E. 2022. 106. 065301

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MISC (2)：

Satoru TOKUDA, Takeshi NAKANISHI, Takafumi SATO. Exhaustive Analysis of Angle-resolved Photoemission Spectra Based on Bayesian Inference. Vacuum and Surface Science. 2023. 66. 3. 152-157
中⻄毅, 中村壮伸, 渡部愛理, 徳田悟. 数理を活用した材料開発の加速へ向けた理論研究. 理論化学会誌フロンティア. 2022. 4. 3. 139-145

Books (1)：

Lectures and oral presentations (16)：

Model selection based on Bayes free energy and its scaling behavior
(The 71st JSAP Spring Meeting 2024 2024)
非線形回帰における対数周辺尤度のスケーリング挙動
(大阪大学データ科学セミナーシリーズ第61回 2024)
Scaling laws for Bayesian inference: Dependence on quantity and quality of observed data
(2023)
Scaling relations between observed data and Occam's razor in Bayesian model selection
(FMfI2023 2023)
Statistical approaches for mathematical modelling based on observed data
(Seminar on interdisciplinary fields between statistical mathematics, informatics and material science 2023)

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Education (2)：

2012 - 2017 The University of Tokyo Graduate School of Frontier Sciences Department of Complexity Science and Engineering
2008 - 2012 Yokohama City University

Professional career (1)：

Work history (6)：

2024/04 - 現在 Kyushu University Institute of Mathematics for Industry (IMI) Associate Professor
2020/04 - 現在 National Institute of Advanced Industrial Science and Technology MathAM-OIL Visiting Researcher
2023/06 - 2024/03 Kyushu University Research Institute for Information Technology Associate Professor
2020/04 - 2023/05 Kyushu University Research Institute for Information Technology Assistant Professor
2017/04 - 2020/03 Tohoku University Advanced Institute for Materials Research Visiting Researcher

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Committee career (1)：

Awards (5)：

2015/10 - 革新的研究開発プログラム (ImPACT)「量子人工脳を量子ネットワークでつなぐ高度知識社会基盤の実現」ベストポスター賞
2015/07 - 物性若手夏の学校分科会最優秀発表
2015/07 - 人工知能学会全国大会優秀賞(口頭発表部門)
2015/07 - 人工知能学会全国大会優秀賞(インタラクティブ発表部門)
2013/03 - IEEE Computational Intelligence Society Japan Chapter Young Researcher Award (Neurocomputing)

Association Membership(s) (1)：

THE PHYSICAL SOCIETY OF JAPAN

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