Takuma Mori
Research And Development Engineer at Honda R&D Co., Ltd.
Wako, Japan
Summary
👤
Senior🎓
Top SchoolTakuma Mori is a Research and Development Engineer with 18 years of experience, currently advancing applied AI and software systems at Honda R&D in Wako, Japan. He combines a strong academic foundation from Nara Institute of Science and Technology with hands-on contributions to high-profile open-source ML projects—most notably improving memory-efficient attention, ControlNet support, and Karras sigma sampling in Hugging Face’s widely used diffusers library. Takuma’s work bridges research and production, focusing on making diffusion models more efficient and practical for image generation pipelines. Known for an “LLM-guided” engineering approach reflected in his GitHub bio, he leverages large models to streamline development and tooling. Colleagues value his blend of deep technical insight and pragmatic experimentation across R&D and industry internships.
18 years of coding experience
Master of Engineering - MEng, Information Science, Master of Engineering - MEng, Information Science at Nara Institute of Science and Technology
Github Skills (13)
diffusion-models10
pytorch10
machine-learning10
diffusion-probabilistic10
stable-diffusion10
deep-learning10
image-generation10
python10
diffusers10
diffusion-probabilistic-models10
net9
flax8
jax8
Programming languages (5)
Github contributions (5)
huggingface/diffusers
Jan 2023 - Jan 2023
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch and FLAX.
Role in this project:
ML Engineer
ML EngineerContributions:53 reviews, 1 commit, 11 PRs in 1 day
Contributions summary:Takuma primarily contributed to the `diffusers` repository, focusing on implementing and improving memory-efficient attention mechanisms. Their work included adding support for xFormers attention operations, incorporating ControlNet models and pipelines, and enabling Karras sigmas for K-diffusion samplers. These contributions enhanced the functionality and efficiency of diffusion models for image generation, specifically targeting Stable Diffusion-based pipelines.
pytorchartdeep-learningimage2imagestate-of-the-art
takuma104/ntlniph
Oct 2008 - Sep 2010
Contributions:52 commits in 1 year 10 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.