PhD Candidate in Informatics, Kyoto University (Oct 2025 – Present) | M.Sc. in Informatics (2025)
Research Interests: Medical AI, Clinical Summarization, Multi-Agent Systems, and Reinforcement Learning.

• Ph.D. in Informatics — Kyoto University
  Oct 2025 – Present
  Laboratory: Takayuki Ito Laboratory
  Graduate School of Informatics
  Title: DoGS SPRING Program Fellow

  • Research on multi-agent reinforcement learning, automated negotiation, and computational mechanism design for collective intelligence systems.

• M.Sc. in Informatics — Kyoto University
  Apr 2023 – Apr 2025
  Laboratory: Medical Informatics Planning Division
  Graduate School of Medicine, Kyoto University Hospital

  • Focused on clinical summarization and trustworthy generative AI for long electronic medical records.

My research lies at the intersection of Large Language Models (LLMs), Reinforcement Learning, and Medical Informatics.
I aim to build trustworthy, interpretable, and resilient AI systems that support real-world healthcare decision-making.

• 🧩 Clinical Summarization and Long-Context Modeling (Kyoto University Hospital) —
  Applied the NBCE method (originally proposed by Su Jianlin) to optimize automatic summarization of long clinical records.
  This work was conducted at the Medical Informatics Planning Division,
  addressing the limited context window of 7B-scale models through dynamic retrieval and TF-IDF-based alignment strategies.

Apr 2025 – Oct 2025
Developed AI-driven scheduling systems for hospital wards, integrating agent-based decision-making into existing HIS infrastructures to enhance nursing efficiency and operational intelligence.

Jul 2021 – Sep 2021
Participated in the China Mobile Enterprise Cloud Storage Project, focusing on module development and large-scale cloud server maintenance (managing ~100 servers).

Oct 2020 – Jun 2022
Represented China in the Microsoft Student Ambassador Asia program. Engaged with global developer communities and contributed to healthcare-related technical projects.

• Zhang, G., Fukuyama, K., Kishimoto, K., & Kuroda, T. (2024).
  Optimizing Automatic Summarization of Long Clinical Records Using Dynamic Context Extension: Testing and Evaluation of the NBCE Method.
  arXiv preprint: arXiv:2411.08586

• Mengyue, F., Lin, Y., Guoqing, Z., et al. (2025).
  Study on subtyping and Traditional Chinese Medicine treatment of depression based on machine learning and text mining.
  Journal of Traditional Chinese Medicine, 45(5), 1152–1163.
  PMCID: PMC12454262

• 🎓 DoGS SPRING Program Fellow (Kyoto University, Division of Graduate Studies)
  Selected under JST’s “Support for Pioneering Research Initiated by the Next Generation (SPRING)” scheme; provides research incentive grants and support for outstanding doctoral students.
• 🧪 Second Prize, China Chemistry Olympiad (Preliminary)
  Certificate
• 🎓 Nishimura International Scholarship Foundation, Spring 2023 Scholar
  Foundation Website

Email: [email protected]
GitHub: dnimo
ORCID: 0009-0007-6956-0814

“Science is built upon curiosity, precision, and empathy — three things I aspire to bring into Medical AI.”