Blanca Li
Product Manager at 微软(中国)有限公司
Haidian District, Beijing, China
Summary
🤩
Rockstar🎓
Top SchoolBlanca Li is a product manager with six years of experience based in Haidian District, Beijing, currently shaping products at Microsoft China. She combines a technical foundation in intelligent science and management science from Beijing University of Posts and Telecommunications and Zhejiang University with hands-on ML engineering work in recommendation systems. Notably, she contributed to the DKN news recommendation model and AzureML deployment artifacts in the popular recommenders repo, evidencing both algorithmic understanding and deployment awareness. At Microsoft she bridges product strategy and engineering execution, focusing on data-driven features that scale. Her background enables her to translate complex ML models into usable product experiences while keeping attention to detail in maintenance and operations. Colleagues describe her as a pragmatic PM who leans on technical credibility to drive cross-functional alignment.
7 years of coding experience
智能科学与技术, 智能科学与技术 at 北京邮电大学硕士, 管理科学与工程, 硕士, 管理科学与工程 at 浙江大学
Github Skills (12)
machine-learning10
deeplearning-ai10
recommendation-engine10
recommender10
recommendation-system10
deep-learning10
python10
data-science10
recommender-system10
azure-machine-learning9
tensorflow9
jupyter-notebook8
Programming languages (5)
Github contributions (5)
recommenders-team/recommenders
May 2020 - Jan 2021
Best Practices on Recommendation Systems
Role in this project:
ML Engineer
ML EngineerContributions:11 commits, 5 PRs, 5 comments in 8 months
Contributions summary:Blanca contributed to the DKN model, a deep learning model for news recommendation, by merging updates, updating module specs, and fixing links. These commits demonstrate work related to integrating the DKN model. The user also updated the AzureML designer module notebook and conda file which indicates some involvement in deployment and operation. Furthermore, fixing the copyright further shows attention to detail and maintenance of the repository.
recommendation-systemmachine-learningrecommenderrankingdeep-learning
Azure/AzureMachineLearningGallery
Oct 2020 - May 2022
Azure Machine Learning Gallery enables our growing community of developers and data scientists to share their machine learning pipelines, components, etc. to accelerate productivity in the machine learning lifecycle.
Contributions:72 PRs, 45 pushes in 1 year 6 months
azure-machine-learningmachine-learning
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