WENG IAN CHAN
Weng Ian Chan
Ianna
Doctoral Student, Computer Vision Lab, The University of Osaka

I am a doctoral student in the Computer Vision Laboratory at The University of Osaka, Japan. My research focuses on computer vision and generative models, with a particular interest in controllable image and video synthesis, diffusion models, and their applications.

Generative models Image synthesis Image / video editing Diffusion models
Osaka U email · GitHub · Google Scholar Linkedin

About & Research Interests

About me
I am currently a doctoral student in Multimedia Engineering at the University of Osaka, supported by the University of Osaka Fellowship for Information and AI Technologies. I have over four years of experience working with advanced image synthesis techniques, including diffusion models and GANs, and enjoy bridging theory, implementation, and practical applications across different domains.
Research interests
  • Controllable image and video synthesis
  • Latent-space editing and exploration
  • Diffusion and GAN models
  • Fairness and robustness in generative models
  • Applications to medical imaging
Education
  • PhD in Information Science
    Multimedia Engineering, The University of Osaka, Japan
    Apr 2023 – present (expected Oct 2026)
  • Master of Information Science
    Multimedia Engineering, The University of Osaka, Japan
    Apr 2021 – Mar 2023
  • Bachelor of Engineering
    Electronic and Information Engineering, The University of Osaka, Japan
    Apr 2017 – Mar 2021
Skills
  • Programming: Python
  • Libraries: PyTorch, NumPy, Pandas, OpenCV, Accelerate, Diffusers
  • Technologies: Linux, CUDA, Docker, Git, LaTeX

Selected Publications

Instance-wise Distribution Control of Text-to-image Diffusion Models
Weng Ian Chan, Hiroaki Santo, Yasuyuki Matsushita, Fumio Okura
Pattern Recognition, vol. 172, part C, 2026, article 112614.
Fine-tuning text-to-image diffusion models to control multi-instance distributions and improve representation of underrepresented groups. Paper
Quantifying the recovery process of skeletal muscle on hematoxylin and eosin-stained images via learning from label proportion
Yu Yamaoka, Weng Ian Chan, Shigeto Seno, Kanako Iwamori, So-ichiro Fukada, Hideo Matsuda
Scientific Reports, 14(1):27044, 2024.
Applies learning from label proportion to quantify skeletal muscle recovery on hematoxylin and eosin-stained images, enabling weakly supervised analysis of tissue-level recovery processes. Paper
Learning from Similarity Proportion Loss for Classifying Skeletal Muscle Recovery Stages
Yu Yamaoka, Weng Ian Chan, Shigeto Seno, Soichiro Fukada, Hideo Matsuda
MICCAI Workshop on Advancing Data Solutions in Medical Imaging AI (ADS-MIA), 2024.
A label-proportion-based learning approach for assessing skeletal muscle recovery, combining weak supervision with medical imaging. Paper

Experience

Research Experience
  • Research Assistant – The University of Osaka
    Apr 2023 – present
  • Visiting Scholar – University of California, Merced (Prof. Ming-Hsuan Yang’s Lab)
    Nov 2024 – Mar 2025
  • Research Intern – CyberAgent, Inc.
    Jul 2024 – Nov 2024
  • Research Intern – rinna Co., Ltd.
    Aug 2021 – Sep 2021

Awards & Scholarships

Awards
  • Audience Award, MIRU 2025
    FreeEyeglass: Training-free and Mask-free Eyeglass Transfer for Facial Videos
  • Student Encouragement Award, MIRU 2025
  • Audience Award, MIRU 2024
    Instance-wise Distribution Control of Text-to-image Diffusion Models
  • Interactive Presentation Award, MIRU 2023
    Fine-grained Facial Image Manipulation via Latent Space Decomposition.
  • Excellent Research Award for Female Graduate Students
    The University of Osaka, 2023
Scholarships & Fellowships
  • The University of Osaka Fellowship for Information and AI Technologies
    2023 – 2025
  • Japanese Government (MEXT) Scholarship – Research Student
    2021 – 2023
  • Japanese Government (MEXT) Scholarship – Undergraduate Student
    2016 – 2021

Contact

Email
chan.wengian{at}ist.osaka-u.ac.jp
(replace {at} with @)
Mailing address
Computer Vision Laboratory
Graduate School of Information Science and Technology
The University of Osaka
1-5 Yamadaoka, Suita, Osaka 565-0871, Japan