Yukinori Yamamoto

Waseda University · Tokyo, Japan · yukinoriyamamoto@akane.waseda.jp

I am a student researcher with a strong interest in exploring the practical applications of autonomous systems using machine learning. My research spans Computer Vision, Computer Graphics, and Physical Intelligence. Pursuing a major in Intermedia Art and Science, I am driven to develop practical AI systems that contribute meaningfully to society. I am affiliated with Prof. Ogata's Laboratory, AIST AIRC (working under Dr. Hirokazu Nosato and Dr. Hirokatsu Kataoka), and cvpaper.challenge. I also collaborate with Dr. Tsukasa Fukusato and Dr. Kazuya Nishimura.

Experience

Technical Trainee (Intern)

Human-AI Collaborative Systems Research Team, Artificial Intelligence Research Center (AIRC) · National Institute of Advanced Industrial Science and Technology (AIST) — Japan

Conducting research on training methodologies for 3D medical image segmentation models under the guidance of Dr. Hirokazu Nosato.

Aug 2025 – Present

Contributor (Google Summer of Code)

RenAIssance (Open Source) — Remote

Researched and developed OCR models for historical documents as part of Google Summer of Code. The project concluded upon completion of the program term.

May 2025 – Sep 2025

AI Engineering Intern

AI Technology Department · Ghelia Inc. — Japan

Implemented reinforcement learning and mathematical optimization algorithms for AI development projects.

Sep 2024 – May 2025

Contributor (Google Summer of Code)

RenAIssance (Open Source) — Remote

Researched and developed OCR models for historical documents as part of Google Summer of Code. The project concluded upon completion of the program term.

May 2024 – Sep 2024

Education

Waseda University

Bachelor of Engineering
Department of Intermedia Art and Science
Expected Graduation: March 2027

Skills

Programming Languages & Tools
Expertise
  • Python — 10+ years of experience
  • Deep Learning — 3+ years of experience
  • Computer Vision & Image Segmentation
  • Reinforcement Learning & Mathematical Optimization
  • OCR & Document AI

Publications

  • Yamamoto, Y., Nishimura, K., Fukusato, T., Nosato, H., Ogata, T., & Kataoka, H. (2026). FDIF: Formula-Driven Supervised Learning with Implicit Functions for 3D Medical Image Segmentation. arXiv preprint. https://arxiv.org/abs/2603.23199

  • Khan, A., Rai, U., Singh, S. S., Yamamoto, Y., Ibarreche, X. G., Meadows, H., & Gleyzer, S. (2024). OCR Approaches for Humanities: Applications of Artificial Intelligence/Machine Learning on Transcription and Transliteration of Historical Documents. Digital Studies in Language and Literature, 1(1–2), 85–112. https://doi.org/10.1515/dsll-2024-0013

Awards

  • Excellence Award — The 4th Hoshi Awards, Junior Category (2017)
    View Award