Personnel Information

写真a

MORIOKA HIROSHI


Title

Associate Professor

Field

Field of Data Science

Mail Address

E-mail address

Homepage URL

https://sites.google.com/view/hiroshimorioka/

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Research Interests 【 display / non-display 】

  • Data-driven

  • Deep learning

  • Representation learning

  • Nonlinear model

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Graduating School 【 display / non-display 】

  • Kyoto University， Graduate School of Informatics， Systems Science

    University， 2015.03， Graduated

  • Tokyo Institute of Technology， The Interdisciplinary Graduate School of Science and Engineering， Computational Intelligence and Systems Science

    University， 2011.03， Graduated

  • Tokyo Institute of Technology， Faculty of Engineering， Department of Control and Systems Engineering

    University， 2009.03， Graduated

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Campus Career 【 display / non-display 】

  • Shiga University Faculty of Data science Department of Data science，Associate Professor， 2025.04 - Now

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External Career 【 display / non-display 】

  • RIKEN Center for Advanced Intelligence Project， Researcher， 2023.04 - 2025.03

  • RIKEN Center for Advanced Intelligence Project， Postdoctoral Researcher， 2019.04 - 2023.03

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Research Areas 【 display / non-display 】

  • Informatics / Intelligent informatics

  • Informatics / Soft computing

  • Informatics / Intelligent informatics

  • Informatics / Soft computing

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Papers 【 display / non-display 】

  • Causal Representation Learning Made Identifiable by Grouping of Observational Variables， Proceedings of The Forty-first International Conference on Machine Learning (ICML2024)， 2024.07, Hiroshi Morioka, Aapo Hyvärinen

    ， Single Author

    Authorship：Lead author,　Corresponding author  

  • Connectivity-contrastive learning: Combining causal discovery and representation learning for multimodal data， Proceedings of The 26th International Conference on Artificial Intelligence and Statistics (AISTATS) (p.3399 - 3426) ， 2023.04, Hiroshi Morioka, Aapo Hyvärinen

    Research paper (international conference proceedings)， Single Author

    Authorship：Lead author  

  • Independent Innovation Analysis for Nonlinear Vector Autoregressive Process， Proceedings of The 24th International Conference on Artificial Intelligence and Statistics (AISTATS) (p.1549 - 1557) ， 2021.04, Hiroshi Morioka, Hermanni Hälvä, Aapo Hyvärinen

    Research paper (international conference proceedings)， Single Author

    Authorship：Lead author  

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Research Grants & Projects 【 display / non-display 】

  • ，Early-Career ScientistsEarly-Career Scientists，2022.04 - 2025.03

  • ，Predicting human behavior by combining brain and behavioral measurements，Early-Career ScientistsEarly-Career Scientists，2019.04 - 2022.03，Japan Society for the Promotion of Science

    We developed a novel analysis framework for general nonlinear dynamics. The conventional frameworks generally assumed linear dynamics or additive innovation models, which can be restrictive for their applications to complex dynamics including the human brain. Our new framework, unsupervised representation learning based on deep learning with theoretical justification, is designed for such general dynamical models, and gives very general tools for analyzing them.

  • ，OtherGrant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area)，2019.04 - 2021.03，Japan Society for the Promotion of Science

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