Case Study (Placeholder)
Outline problem → design → implementation → evaluation.
Yuhei Yamada
I currently work on automating operations and conducting R&D in the entertainment domain.
Previously, I focused on the education sector, building automated question generation, auto-grading, and document proofreading systems that leveraged AI to improve efficiency and quality.
My primary interests include Explainable AI (XAI), large language models (LLMs), and data science.
I strive to learn new technologies continuously, share insights proactively, and I am a Kaggle Expert with multiple medals, including several golds.
How I Deliver
Problem-first scoping
Interview stakeholders, observe workflows, and align the team on PoC-to-production plans with measurable outcomes.
Workflow design with LLMs
Map processes end-to-end and blend LLMs with classic ML to ship automation pipelines that stay safe and maintainable.
Continuous knowledge sharing
Publish write-ups and host sessions so teams capture learnings and make better engineering decisions together.
Skill Map
Infrastructure & Ops Toolchain
I invest in the DevOps stack needed to keep AI products reliable and secure.
Git
GitLab CI
AWS (ECS / Lambda / S3)
Docker
Nginx
Certbot
Latest
Learning Project (Placeholder)
Small web app or analysis notes.
Code Reading/Improvement (Placeholder)
Understanding existing repos and small improvements.