Guanyue Bian
Backend Software Engineer at Robinhood
California, United States
Summary
🤩
Rockstar🎓
Top SchoolGuanyue Bian is a backend software engineer with eight years of experience building data-intensive systems and production services, currently working at Robinhood in California. He combines industry experience at ByteDance with academic research as a PhD candidate at UCSD (McAuley Lab) and prior research work at the University of Alberta, focusing on recommender systems and large language models. Guanyue contributed significant backend work to RecBole—an established open-source recommendation library—improving data pipelines, negative sampling, and dataset efficiency. Trained with an MEng from UC Berkeley and a CS bachelor from Renmin University, he blends rigorous research methods with practical engineering for scalable ML-driven infrastructure. Colleagues can expect an engineer who moves fluidly between research-grade algorithms and production-grade data processing.
8 years of coding experience
1 year of employment as a software developer
Master of Engineering - MEng, Computer Science, Master of Engineering - MEng, Computer Science at University of California, BerkeleyBachelor's degree, Computer Science, Bachelor's degree, Computer Science at Renmin University of China
Github Skills (6)
python10
data-processing10
pytorch9
pandas8
data-structure7
data-structures7
Programming languages (7)
Github contributions (5)
RUCAIBox/RecBole
Jun 2020 - Oct 2022
A unified, comprehensive and efficient recommendation library
Role in this project:
Back-end Developer
Back-end DeveloperContributions:54 reviews, 667 commits, 49 PRs in 2 years 4 months
Contributions summary:Guanyue contributed to the data and dataset components of the RecBole library. Their work involved implementing data processing pipelines, including splitting and filtering data. They made significant changes to the data and dataset files, introducing new functionality for negative sampling and other data transformations. The user appears to have been involved in improving the efficiency of data processing within the library.
pytorchrecommenderdeep-learningcollaborative-filteringsequential-recommendation
hyp1231/awesome-llm-powered-agent
Jul 2023 - Mar 2025
Awesome things about LLM-powered agents. Papers / Repos / Blogs / ...
Contributions:3 reviews, 45 PRs, 118 pushes in 1 year 8 months
chatgptembodied-agentembodied-aifoundation-modelfoundation-models
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