Zipeng Xiao
Assistant Engineer at CSWADI (China SouthWest Architectural Design and Research Institute Corp.LTD)
Chengdu, Sichuan, China
Summary
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Rockstar🎓
Top SchoolZipeng Xiao is an assistant engineer blending architectural design with a strong interest in data, algorithms, and computer science, backed by six years of interdisciplinary experience. Trained in architecture at Xi’an Jiaotong-Liverpool University and the Universities of Liverpool and Edinburgh, he applies analytical rigor to building design, sustainability assessments, and technical drawing for projects like hotels and offices. At CSWADI he focuses on green building evaluations, prefabrication, and carbon neutrality efforts, translating complex energy and regulatory data into actionable construction documents. His open-source contributions to the OneFlow deep learning framework—adding tests, new loss and activation interfaces, and improving code quality—reveal a practical software engineering streak not obvious from his architecture resume. Comfortable in international teams and field research, he brings a rare mix of computational tooling and hands-on architectural practice to sustainability-minded design challenges.
6 years of coding experience
Bachelor of Architecture - BA (Hons), architecture, Bachelor of Architecture - BA (Hons), architecture at 英国利物浦大学Bachelor of Architecture - BEng, architecture, Bachelor of Architecture - BEng, architecture at 西交利物浦大学Master of Science - MS, Architectural and Urban Design, Master of Science - MS, Architectural and Urban Design at 英国爱丁堡大学
Stackoverflow
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Github Skills (7)
neural-network10
pytorch10
machine-learning10
deep-learning10
python10
testing9
cuda7
Programming languages (4)
Github contributions (5)
Oneflow-Inc/oneflow
Jul 2021 - Dec 2022
OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.
Role in this project:
ML Engineer
ML EngineerContributions:17 reviews, 17 commits, 18 PRs in 1 year 5 months
Contributions summary:Zipeng contributed to the OneFlow deep learning framework, focusing on enhancing the testing infrastructure and adding new features. Their commits included implementing tests for various modules such as cat, dropout, and RNN, demonstrating a focus on ensuring the framework's functionality. They also added interfaces for MSE loss and quick GELU activation, which highlights their role in extending the framework's capabilities. Furthermore, their contributions involved code formatting and refactoring, ensuring code quality and maintainability.
caffe2tensorflowframework-learningchainerdeep-learning-framework
Oneflow-Inc/text
Oct 2021 - Apr 2022
Data loaders and abstractions for text and NLP
Contributions:1 review, 40 commits, 9 PRs in 5 months
nlpabstractionsnatural-language-processingloaders
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