Sirui Ding
Postdoctoral Scholar at 美国斯坦福大学
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolSirui Ding is a computational biomedicine researcher and software engineer with 8 years of experience developing AI methods for healthcare and life sciences. Currently a postdoctoral scholar at Stanford's Department of Biomedical Data Science after a postdoc at UCSF, she combines rigorous PhD training from Texas A&M with hands-on engineering—contributing to notable open-source AutoML work in the AutoKeras project that spans deep learning preprocessing, model layers, and tabular workflows. Based in San Francisco, she bridges academic research and production-quality ML, focusing on practical model building and data-driven biomedical insights. Her background reflects a pattern of moving between top research labs and community-facing engineering, enabling rapid translation of novel algorithms into reproducible tools.
8 years of coding experience
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at Wuhan UniversityDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Texas A&M University
Github Skills (10)
keras10
machine-learning10
deeplearning-ai10
deep-learning10
tensorflow10
automl10
python10
preprocess9
neural-architecture-search9
preprocessing9
Programming languages (2)
Github contributions (5)
keras-team/autokeras
Feb 2019 - Dec 2019
AutoML library for deep learning
Role in this project:
ML Engineer
ML EngineerContributions:5 commits, 17 PRs, 165 pushes in 10 months
Contributions summary:Sirui contributed to the `autokeras` library, which focuses on AutoML for deep learning. Their commits primarily involve updates to various files related to the core functionality of the library, including preprocessing, model definitions, and layers. Significant modifications were made to files like `deepvoice3.py`, `preprocessor.py`, and `layers.py`, indicating active involvement in improving and refining the deep learning model building and training processes. The user's work also touched on tabular data processing, indicating a broad understanding of AutoKeras's capabilities.
pytorchpythondeep-learningautomated-machine-learningneural-architecture-search
Davidsirui/How-to-write-a-paper-for-your-open-source-project
Nov 2019 - Feb 2020
Contributions:30 commits, 29 pushes, 1 branch in 2 months
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