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RIKEN Center for Biosystems Dynamics Research Laboratory for Multimodal AI Framework

Team Director: Ryosuke Kojima (Ph.D.)

Research Summary

Ryosuke Kojima

The Laboratory for Multimodal AI Framework is developing AI technologies to handle multimodal and hierarchical data, such as images, natural language, acoustic signals, time-series data, and structured data, while applying these technologies to address diverse challenges in life sciences. Specifically, we focus on developing modeling techniques for complex data and large-scale foundational models. Additionally, we aim to translate these advancements into tools and platforms, ultimately deploying them in real-world applications.

Main Research Fields

  • Informatics

Related Research Fields

  • Chemistry
  • Complex Systems
  • Interdisciplinary Science & Engineering
  • Mathematical & Physical Sciences
  • Biology
  • Machine learning
  • Data science
  • Bioinformatics

Keywords

  • Artificial intelligence
  • Machine learning
  • Bioinformatics
  • Cheminformatics
  • Medical AI

Selected Publications

Papers with an asterisk(*) are based on research conducted outside of RIKEN.

  • 1. *R.Kojima, Y.Okamoto.
    "Learning deep input-output stable dynamics."
    In Advances in Neural Information Processing Systems (NeurIPS), Vol. 35 pp. 8187-8198, Nov., 2022.
  • 2. *S.Ishida, K.Terayama, R.Kojima, K.Takasu, Y.Okuno.
    "AI-Driven Synthetic Route Design Incorporated with Retrosynthesis Knowledge"
    In Journal of Chemical Information and Modeling, 2022.
  • 3. *K.Nakamura, R.Kojima, E.Uchino, K.Ono, M.Yanagita, K.Murashita, K.Itoh, S.Nakaji, Y.Okuno.
    "Health improvement framework for actionable treatment planning using a surrogate Bayesian model."
    In Nature Communications, Nature Publishing Group, Vol. 12 No. 1 pp. 1-15, 2021.
  • 4. *R.Kojima, S.Ishida, M.Ohta, H.Iwata, T.Honma, Y.Okuno.
    "kGCN: a graph-based deep learning framework for chemical structures"
    In Journal of Cheminformatics, Springer, Vol. 12 pp. 1-10, 2020.
  • 5. *R. Kojima, T. Sato.
    "Learning to rank in PRISM"
    In International Journal of Approximate Reasoning, Vol. 93 pp. 561 - 577, 2018.
  • 6. *R. Kojima, O. Sugiyama, K. Hoshiba, R. Suzuki, K. Nakadai.
    "HARK-Bird-Box: A Portable Real-Time Bird Song Scene Analysis System"
    Intelligent Robots and Systems (IROS), 2018 IEEE/RSJ International Conference on, Oct., 2018.
  • 7. *R.Kojima, O.Sugiyama, R.Suzuki, K.Nakadai, C. E.Taylor.
    "Semi-Automatic Bird Song Analysis by Spatial-Cue-Based Integration of Sound Source Detection, Localization, Separation, and Identification."
    "Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on, Oct., 2016.
  • 8. *R.Kojima, T.Sato.
    "Goal and Plan Recognition via Parse Trees Using Prefix and Infix Probability Computation"
    Inductive Logic Programming, Springer, 2015.

Related Links

Lab Members

Principal investigator

Ryosuke Kojima
Team Director

Core members

Yoshinobu Igarashi
Senior Research Scientist
Benjamin Yen
Postdoctoral Researcher
Kazunobu Matsubara
Technical Staff II
Tatsuya Sagawa
Student Trainee

Careers

Position Deadline
Seeking a Technical Staff II (K24097) Open until filled
Seeking Research Scientist or Postdoctoral Researcher (K24068) Open until filled

Contact Information

2F, Integrated Innovation Building (IIB)
6-7-1, Minatojima minami-machi, Chuou-ku, Kobe,
Hyogo, 650-0047 JAPAN
Email: ryosuke.kojima@riken.jp

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