Rchr
J-GLOBAL ID:201801015406549700   Update date: Jan. 12, 2025

Miyamoto Takashi

ミヤモト タカシ | Miyamoto Takashi
Affiliation and department:
Homepage URL  (1): http://www.ccn.yamanashi.ac.jp/~tmiyamoto/
Research field  (3): Mathematical informatics ,  Disaster prevention engineering ,  Structural and seismic engineering
Research keywords  (3): applied mechanics ,  data science ,  earthquake engineering
Research theme for competitive and other funds  (11):
  • 2021 - 2024 A New AI Method for Bridge Inspection and Diagnosis that Combines CNN with Highly Accurate Damage Detection and Expertises
  • 2019 - 2024 スパースな地震観測網による地盤-構造物系の地震時挙動の高精度予測手法の開発
  • 2019 - 2023 Development of a heavy rainfall prediction method combining numerical weather prediction models and deep learning methods
  • 2018 - 2022 様々な情報源から得られるヘテロデータのマルチモーダル学習による地震被害分布の推定
  • 2019 - 2021 衛星リモートセンシングから得られる時空間ビッグデータの機械学習による地震被害の判別
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Papers (37):
  • Shitao Zheng, Takashi Miyamoto, Shingo Shimizu, Ryohei Kato, Koyuru Iwanami. Coordinate-Transformed Dynamic Mode Decomposition for Short-Term Rainfall Forecasting. IEEE Transactions on Geoscience and Remote Sensing. 2024. 62. 1-17
  • KINOSHITA Kosuke, YANO Yukihiro, KUMURA Takahiro, MIYAMOTO Takashi, CHUN Pang-jo. Comparative analysis of time-series InSAR bridge deformation analysis and structural simulation for a hinged PC bridge. Artificial Intelligence and Data Science. 2024. 5. 3. 730-739
  • Shitao Zheng, Takashi Miyamoto, Koyuru Iwanami, Shingo Shimizu, Ryohei Kato. Hybrid Scheme of Kinematic Analysis and Lagrangian Koopman Operator Analysis for Short-Term Precipitation Forecasting. Journal of Disaster Research. 2022. 17. 7. 1140-1149
  • Hidetaka Saomoto, Takashi Miyamoto. GENERATING MACHINE LEARNING DATASETS ON DAMAGE IDENTIFICATION USING FINITE ELEMENT BRIDGE MODEL. Journal of Japan Society of Civil Engineers, Ser. A1 (Structural Engineering & Earthquake Engineering (SE/EE)). 2022. 78. 4. I_10-I_21
  • Shitao Zheng, Takashi Miyamoto, Shingo Shimizu, Ryohei Kato, Koyuru Iwanami. Physics-Informed Data-Driven Model for Short-Term Precipitation Prediction Using Radar-Observed Big Data. IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. 2022
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MISC (34):
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Education (4):
  • 2009 - 2012 The University of Tokyo Graduate School of Engineering Doctoral Course, Department of Civil Engineering
  • 2007 - 2009 The University of Tokyo Graduate School of Engineering Master Course, Department of Civil Engineering
  • 2005 - 2007 The University of Tokyo Faculty of Engineering Department of Civil Engineering
  • 2003 - 2005 The University of Tokyo College of Liberal Arts and Sciences Junior Division Natural Sciences I
Professional career (1):
  • 博士(工学) (東京大学)
Work history (4):
  • 2021/04 - 現在 German Research Center for Artificial Intelligence Visiting Scholar
  • 2020/02 - 現在 University of Yamanashi Faculty of Engineering Department of Civil and Environmental Engineering Associate Professor
  • 2012/07 - 2020/01 University of Yamanashi Department of Civil & Environmental Engineering assistant professor
  • 2012/04 - 2012/06 University of Illinois Urbana Champaign visiting researcher
Awards (5):
  • 2020/12 - 土木学会構造工学委員会 構造工学でのAI活用に関する研究小委員会 AI・データサイエンス論文賞 パターン認識と法則発見のデータサイエンス
  • 2020/10 - Japan Society of Civil Engineering Presentation Award on 2020 JSCE Applied Mechanics Symposium
  • 2017/08 - Best Presentation Award, IMEC2017
  • 2014/10 - Outstanding Paper Award, Built Environment Project and Asset Management
  • 2010/08 - Applied Mechanics Committee, Japan Society of Civil Engineering Best Paper Award from JSCE Applied Mechanics Committee
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