Lin zihan
Beijing, China
Summary
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RockstarZihan Yu is a product manager with nine years of cross-cultural experience building data-informed products at ByteDance and Meituan, grounded in an MSc from Oxford and a background in Chinese literature and US exchange studies. She blends product strategy with hands-on technical fluency—contributing back-end and data-science code to the RecBole recommendation library, improving configuration, device support, and logging for an established open-source recommender toolkit. Comfortable operating at the intersection of analytics, engineering, and content, she has also worked in media programming and research roles that sharpen her user-centric storytelling and stakeholder communication. Known for translating complex data and policy insights into actionable product roadmaps, she brings a pragmatic, research-driven approach to scaling personalized experiences.
8 years of coding experience
Github Skills (7)
configuration-management10
logging10
python10
deeplearning-ai9
recommendation-system9
deep-learning9
pytorch9
Programming languages (2)
Github contributions (5)
RUCAIBox/RecBole
Jun 2020 - Oct 2021
A unified, comprehensive and efficient recommendation library
Role in this project:
Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:15 reviews, 402 commits, 23 PRs in 1 year 3 months
Contributions summary:Lin made several commits focused on the configuration and setup of the RecBole library, specifically targeting the configuration management module. The user created a Config class to load predefined hyper-parameters and introduced support for device configurations. The user also added and tested a logger module for debugging and information display. Furthermore, the user improved the command line arguments parsing module.
pytorchrecommenderdeep-learningcollaborative-filteringsequential-recommendation
linzihan-backforward/RecBole
Nov 2020 - Nov 2022
A unified, comprehensive and efficient recommendation library
Contributions:53 PRs, 59 pushes, 4 branches in 2 years
recommendationmachine-learningpersonalizationrecallrecommendation-engine
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