Rchr
J-GLOBAL ID:201801009375893814   Update date: Feb. 24, 2024

Suzuki Yuta

スズキ ユウタ | Suzuki Yuta
Affiliation and department:
Homepage URL  (1): https://resnant.github.io
Research field  (1): Applied materials
Research keywords  (6): Black-box optimization ,  deep learning ,  X-ray diffraction ,  Knowledge Discovery ,  Machine Learning ,  Materials Informatics
Research theme for competitive and other funds  (2):
  • 2019 - 2022 機械学習と材料データベースを活用したハイスループット計測データの自動解析
  • 2018 - 2020 Development of Data Analysis Method for On-the-fly Crystal System Prediction
Papers (17):
  • Yuta Suzuki, Tatsunori Taniai, Kotaro Saito, Yoshitaka Ushiku, Kanta Ono. Self-supervised learning of materials concepts from crystal structures via deep neural networks. Mach. Learn. Sci. Technol. 2022. 3. 4. 45034-45034
  • Yusaku Nakajima, Masashi Hamaya, Yuta Suzuki, Takafumi Hawai, Felix von Drigalski, Kazutoshi Tanaka, Yoshitaka Ushiku, Kanta Ono. Robotic Powder Grinding with a Soft Jig for Laboratory Automation in Material Science. 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2022
  • Naoya Chiba, Yuta Suzuki, Tatsunori Taniai, Ryo Igarashi, Yoshitaka Ushiku, Kotaro Saito, Kanta Ono. Neural Structure Fields with Application to Crystal Structure Autoencoders. CoRR. 2022. abs/2212.13120
  • Takashi Kamiyama, Kazuma Hirano, Hirotaka Sato, Kanta Ono, Yuta Suzuki, Daisuke Ito, Yasushi Saito. Application of machine learning methods to neutron transmission spectroscopic imaging for solid-liquid phase fraction analysis. Applied Sciences (Switzerland). 2021. 11. 13
  • Yuta Suzuki, Hideitsu Hino, Takafumi Hawai, Kotaro Saito, Masato Kotsugi, Kanta Ono. Symmetry prediction and knowledge discovery from X-ray diffraction patterns using an interpretable machine learning approach. SCIENTIFIC REPORTS. 2020. 10. 1
more...
MISC (3):
  • 鈴木雄太, 鈴木雄太, 尾崎嘉彦, 尾崎嘉彦, 羽合孝文, 斉藤耕太郎, 斉藤耕太郎, 大西正輝, 小野寛太, 小野寛太. ブラックボックス最適化を用いたリートベルト解析の自動化. 日本放射光学会年会・放射光科学合同シンポジウム(Web). 2021. 34th
  • 鈴木雄太, 尾崎嘉彦. Applications of Bayesian Optimization. 電子情報通信学会技術研究報告(Web). 2021. 120. 395(IBISML2020 34-61)
  • 鈴木雄太, 鈴木雄太, 小野寛太, 小野寛太. Machine learning applications for data analysis in quantum beam experiments. 日本表面真空学会学術講演会要旨集(Web). 2020. 2020
Lectures and oral presentations  (6):
  • Automated Lattice Constant Estimation of X-ray Diffraction by Ensemble Learning
    (The 5th International Conference on Electronic Materials and Nanotechnology for Green Environment 2018)
  • Machine Learning-based Crystal Structure Prediction for X-Ray Microdiffraction
    (The 14th International Conference on X-Ray Microscopy 2018)
  • Extraction of Physical Parameters from X-ray Spectromicroscopy Data Using Machine Learning
    (The 14th International Conference on X-Ray Microscopy 2018)
  • Classification of Crystal Structure from X-ray Diffraction Patterns using Machine Learning
    (The 13th International Conference on Synchrotron Radiation Instrumentation 2018)
  • Estimation of Physical Parameters using Dimensionality Reduction of X-Ray Absorption Spectra
    (The 13th International Conference on Synchrotron Radiation Instrumentation 2018)
more...
Education (3):
  • 2019 - 2022 The Graduate University for Advanced Studies School of High Energy Accelerator Science Department of Materials Structure Science
  • 2017 - 2019 Tokyo University of Science
  • 2013 - 2017 Tokyo University of Science
Professional career (1):
  • Doctor of Science (The Graduate University for Advanced Studies)
Awards (4):
  • 2022/03 - The Graduate University of Advanced Studies SOKENDAI Award Crystal Structure Analysis and Visualization of Materials Space Using Machine Learning
  • 2019/03 - Tokyo University of Science TUS Incentive Award (Mathematics and Physics)
  • 2019/03 - Tokyo University of Science TUS Award 2018
  • 2017/03 - The best poster award Development of Pulsed Laser Deposition Method for Fabrication of Metallic Thin Films
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