Personnel Information

写真b

KONNO TOMOHIKO

Organization
School of Policy Studies
Research Fields, Keywords
Artificial Intelligence and Copyright Law, statistical physics, deep learning, 機械学習, データサイエンス, ゲーム理論, 経済学, 複雑ネットワーク, AI, Machine Learning Physics, artificial intelligence
Mail Address
tomo.konno@kwansei.ac.jp
Syllabus information URL
https://syllabus.kwansei.ac.jp/uniasv2/UnSSOLoginControlFree?REQ_ACTION_DO=/AGA030PLS01Action.do?REQ_FUNCTION_JUMP_START_FLG=1&SLB_LINK_DISP_FLG=689&TCH_NO=230016&REQ_PRFR_FUNC_ID=AGA030
SDGs Related Goals
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Graduating School 【 display / non-display 】

  • Graduating School:The University of Tokyo
    Faculty:Dept. of Engineering
    Course / Major:Applied Physics

    Kind of school:University
    Completion status:Graduated
    Country location code:Japan

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Graduate School 【 display / non-display 】

  • Graduate school:The University of Tokyo

    Course completed:Doctor's Course
    Completion status:Completed
    Country:Japan

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Studying abroad experiences 【 display / non-display 】

  • Name of institution: Princeton University

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Degree 【 display / non-display 】

  • Degree name:博士
    Classified degree field:Humanities & Social Sciences / Economic theory
    Conferring institution:The University of Tokyo
    Acquisition way:Coursework

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Career 【 display / non-display 】

  • Affiliation:Kwansei Gakuin University
    Department:School of Policy Studies
    Title:Associate Professor

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Research Areas 【 display / non-display 】

  • Research field:Natural Science / Mathematical physics and fundamental theory of condensed matter physics

  • Research field:Informatics / Intelligent informatics

  • Research field:Humanities & Social Sciences / Economic statistics

  • Research field:Humanities & Social Sciences / Economic theory

  • Research field:Natural Science / Applied mathematics and statistics

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Papers 【 display / non-display 】

  • Language: English
    Title: Deep learning model for finding new superconductors
    Journal name: PHYSICAL REVIEW B  vol.103  (1)
    Date of publication: 2021.01
    Author(s): Tomohiko Konno, Hodaka Kurokawa, Fuyuki Nabeshima, Yuki Sakishita, Ryo Ogawa, Iwao Hosako, Atsutaka Maeda

    DOI: 10.1103/PhysRevB.103.014509
    Type of publication: Research paper (scientific journal)

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  • Language: English
    Title: A condition for cooperation in a game on complex networks
    Journal name: JOURNAL OF THEORETICAL BIOLOGY  vol.269  (1)  (p.224 - 233)
    Date of publication: 2011.01
    Author(s): Tomohiko Konno

    DOI: 10.1016/j.jtbi.2010.10.033
    Type of publication: Research paper (scientific journal)

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  • Language: English
    Title: Network Structure of Japanese Firms. Scale-Free, Hierarchy, and Degree Correlation: Analysis from 800,000 Firms
    Journal name: ECONOMICS-THE OPEN ACCESS OPEN-ASSESSMENT E-JOURNAL  vol.3
    Date of publication: 2009.07
    Author(s): Tomohiko Konno

    Type of publication: Research paper (scientific journal)

  • Language: English
    Title: Deep Learning Estimation of Band Gap with the Reading-Periodic-Table Method and Periodic Convolution Layer
    Journal name: JOURNAL OF THE PHYSICAL SOCIETY OF JAPAN  vol.89  (12)
    Date of publication: 2020.12
    Author(s): Tomohiko Konno

    DOI: 10.7566/JPSJ.89.124006
    Type of publication: Research paper (scientific journal)

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  • Language: English
    Title: SEMI-SUPERVISED LAND COVER CLASSIFICATION USING PI-SAR2 OBSERVATION DATA
    Journal name: IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM  (p.2755 - 2758)
    Date of publication: 2020
    Author(s): Yuya Arima, Shoichiro Kojima, Jyunpei Uemoto, Tomohiko Konno

    DOI: 10.1109/IGARSS39084.2020.9323431
    Type of publication: Research paper (international conference proceedings)

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Research Projects 【 display / non-display 】

  • Research category:学術変革領域研究(A)
    Project year：2023.04 - 2025.03
    Title:深層学習による超伝導体探索

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Presentations 【 display / non-display 】

  • Language:English
    Conference name:35th International Symposium on Superconductivity (ISS2022)
    Holding date：2022.11
    Presentation date：2022.11
    Title:Deep learning model for finding new superconductors
    Presentation type:Oral presentation (invited, special)

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