Yiyuan Yang
Oxford, England, Australia
Summary
🤩
Rockstar🎓
Top SchoolYiyuan Yang is a software engineer and PhD candidate in computer science with seven years of industry and research experience across NLP, multimodal learning, and video codec research. He has interned at top-tier labs including Microsoft and Baidu (working with ERNIE-Bot) and contributed production-focused engineering at Meituan and YIHANG.AI. His open-source work includes implementing seq2seq and transformer machine translation models and experimenting with back-translation in a well-regarded deep learning tutorial repository. Strong mathematical and analytical foundations complement hands-on programming skills, enabling him to bridge scientific research and application development. Based in Oxford with academic roots from USC and Beihang, he brings a research-driven mindset to practical ML and software problems.
7 years of coding experience
1 year of employment as a software developer
Master's degree, computer science, 3.8, Master's degree, computer science, 3.8 at 美国南加州大学Bachelor's degree, Computer Science, 3.65/4.0, Bachelor's degree, Computer Science, 3.65/4.0 at Beihang UniversityDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Technology Sydney
Chinese, English
Github Skills (8)
machine-translation10
transformer10
rnn-model10
deep-learning10
n10
python10
seq2seq10
user-manual9
Programming languages (2)
Github contributions (5)
datawhalechina/leedl-tutorial
Apr 2023 - Dec 2024
《李宏毅深度学习教程》（李宏毅老师推荐👍，苹果书🍎），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases
Role in this project:
ML Engineer
ML EngineerContributions:55 pushes, 12 comments, 6 issues in 1 year 7 months
Contributions summary:Yiyuan contributed to a machine translation project based on the provided commit messages. They implemented a sequence-to-sequence (seq2seq) model using an RNN, likely in Python. The user then focused on improving the model by integrating a transformer architecture, a more advanced approach for machine translation tasks. The final step involved exploring back-translation to further enhance the model's performance.
notesmachine-learningbertchatgptcnn
yyysjz1997/Awesome-TimeSeries-SpatioTemporal-Diffusion-Model
Oct 2023 - Mar 2025
Contributions:121 pushes, 1 branch, 6 comments in 1 year 5 months
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