Youzhi Luo
Applied Scientist at Amazon Web Services (AWS)
California, United States
Summary
🤩
Rockstar🎓
Top SchoolYouzhi Luo is an applied scientist with eight years of experience bridging research and production in graph deep learning and large language model inference. Currently at AWS, he focuses on optimizing LLM inference, drawing on a PhD in Computer Science from Texas A&M and research stints at Google, Fujitsu, and NEC Labs where he developed graph temporal models and molecular potential predictors. He contributes to open-source graph DL tooling—improving documentation and tutorials for the divelab/DIG evaluation module—to make research code more accessible and reproducible. Comfortable both designing algorithms and hardening them for real-world systems, he combines deep academic training with hands-on engineering in California’s AI ecosystem. An understated strength is his attention to clarity: beyond code he elevates usability through clear docs and tutorials that accelerate adoption.
8 years of coding experience
Bachelor of Engineering - BE Automation, Bachelor of Engineering - BE Automation at University of Science and Technology of ChinaDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Texas A&M University
Github Skills (7)
documentation-generator10
sphinx-doc10
sphinx10
documentation10
python8
deeplearning-ai4
deep-learning4
Programming languages (2)
Github contributions (5)
divelab/DIG
Mar 2021 - Oct 2022
A library for graph deep learning research
Role in this project:
Technical Writer
Technical WriterContributions:10 reviews, 38 commits, 2 PRs in 1 year 7 months
Contributions summary:Youzhi primarily focused on improving the documentation of the `dig/ggraph/evaluation` module within the `dig` repository. Their contributions involved adding detailed documentation and comments to the evaluation metric functions, enhancing clarity and usability. This included the addition of docstrings and restructuring existing comments to provide better context for users. Further, the user modified the documentation by updating the rst files, fixing code errors, and adding a tutorial.
explainable-mlpytorchdataminingdeep-learninggraph-deep-learning
lyzustc/lyzustc.github.io
Jul 2019 - Aug 2024
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
Contributions:28 pushes in 5 years 1 month
templategithub-pages-templatemmistakesmistakesjekyll
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