Shurui Gui
Senior Machine Learning Engineer at Roblox
College Station, Texas, United States
Summary
🤩
Rockstar🎓
Top SchoolShurui Gui is a Senior Machine Learning Engineer and PhD student at Texas A&M with eight years of experience building and explaining graph-based deep learning systems. Her research-driven background (4.0 GPA) and internships at NEC Labs, University of Sydney, and Amazon inform a practice that bridges cutting-edge GNN research and production ML. At Roblox she focuses on scalable ML solutions, while her open-source work on the divelab/DIG library emphasizes explainable AI for GNNs, including implementing GNN-LRP and improving explainer documentation. She combines rigorous academic training with hands-on engineering, frequently turning research methods into reproducible code and clearer user-facing explanations. Collected international experience and a top-7% undergraduate degree from University of Science and Technology of China give her a global perspective on complex ML problems.
8 years of coding experience
Bachelor's degree, Computer Science, Top 7%, Bachelor's degree, Computer Science, Top 7% at 中国科学技术大学Doctor of Philosophy - PhD, Computer Engineering, 4.0/4.0, Doctor of Philosophy - PhD, Computer Engineering, 4.0/4.0 at Texas A&M University
Github Skills (8)
pytorch10
machine-learning10
xai10
explainable-artificial-intelligence10
deep-learning10
graph-neural-network10
python10
gnn10
Programming languages (4)
Github contributions (5)
divelab/DIG
Feb 2021 - Nov 2022
A library for graph deep learning research
Role in this project:
ML Engineer
ML EngineerContributions:71 commits, 8 PRs, 39 pushes in 1 year 9 months
Contributions summary:Shurui's commits primarily involve implementing and refining explainable AI (XAI) methods within the context of a graph deep learning research library. Their work focuses on integrating GNN-LRP, a technique for explaining GNN predictions, as evidenced by code changes to the `explainers.py` and related files. They are also working on providing additional documentation to clarify the different methods.
explainable-mlpytorchdataminingdeep-learninggraph-deep-learning
divelab/GOOD
Jun 2022 - Jan 2023
GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]
Contributions:2 releases, 164 commits, 2 PRs in 7 months
benchmarkingbenchmarkgraphout-of-distributiondistribution
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