Tiancheng Yao
Senior Engine Programmer at Tencent Games
Xuhui District, Shanghai, China
Summary
🤩
Rockstar🎓
Top SchoolTiancheng Yao is a Senior Engine Programmer with 11 years’ experience building and optimizing rendering systems for AAA titles and shipping D3D12 ray tracing features at Tencent Games. He has deep expertise in physically based rendering, GPU-driven pipelines, and cross-platform engine work from console and PC to Vulkan on mobile, gained at Ubisoft and Tencent. Tiancheng has hands-on experience modifying engine source (Unreal, Dunia, Unity/Snowdrop) to meet production needs, debug GPU crashes, and migrate heavy lighting workloads to the GPU. Outside of games he contributes to ML tooling—improving a text classification Graph Convolutional Network repo—and writes a hobby path-tracing renderer, reflecting a blend of academic rigor and practical engineering. Based in Shanghai, he combines a gamer’s eye for visual fidelity with a track record of shipping performant, platform-spanning graphics solutions.
11 years of coding experience
5 years of employment as a software developer
Bachelor's Degree, Computer Science and Technology, The Second Prize Scholarship, Bachelor's Degree, Computer Science and Technology, The Second Prize Scholarship at Dalian Nationalities University
English, Chinese
Github Skills (13)
nlp10
deep-learning10
graph-convolutional-networks10
python10
text-classification10
natural-language-processing10
data-processing10
visualizations9
tensorflow9
machine-learning9
visualization9
scikit8
scikit-learn8
Programming languages (2)
Github contributions (5)
yao8839836/text_gcn
Sep 2018 - Jul 2019
Graph Convolutional Networks for Text Classification. AAAI 2019
Role in this project:
ML Engineer
ML EngineerContributions:55 commits, 4 PRs, 47 pushes in 10 months
Contributions summary:Tiancheng primarily focused on enhancing the text classification model. Their contributions included updating data processing scripts, adding visualization tools for word embeddings, and integrating evaluation metrics like precision, recall, and F1-score. They also adjusted the code to handle dataset inputs via arguments and optimized memory usage.
graph-convolutional-networkstext-classificationdeep-learningnlp
yao8839836/ProbaseLDA
Jan 2015 - Aug 2018
Contributions:20 commits, 19 pushes, 1 branch in 3 years 7 months
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