Yan Li
Interactive Designer at NetEase
Nanjing City, Jiangsu, China
Summary
🤩
Rockstar🎓
Top SchoolYan Li is an interactive designer with 14 years of experience based in Nanjing, specializing in AI product interaction and large-scale web platforms. Currently shaping user experiences for AI products at NetEase and previously leading interaction design for cn.made-in-china.com, he blends industrial design training with practical digital product delivery. He holds dual master’s degrees in Industrial Design from Southeast University and Monash University and a B.Eng. in Mechanical Engineering, which informs a systems-minded approach to UX and interaction. Yan also contributes to ML ops work on TensorFlow serving integrations, demonstrating an unusual combination of interaction design sensibility and hands-on model deployment experience. His background suggests strength in translating complex AI capabilities into intuitive user flows while keeping production readiness and evaluation in mind.
14 years of coding experience
Master of Engineering (M.Eng.), Industrial Design, Master of Engineering (M.Eng.), Industrial Design at Southeast UniversityBachelor of Engineering (BEng), Mechanical Engineering, Bachelor of Engineering (BEng), Mechanical Engineering at Southwest UniversityMaster of Industrial Design, Industrial Design, Master of Industrial Design, Industrial Design at Monash University
English, Chinese
Github Skills (8)
tensorflow10
python10
grpc10
machine-learning9
docker8
dockers8
kubernetes-pods7
kubernetes7
Programming languages (6)
Github contributions (5)
caicloud/tensorflow-tutorial
Feb 2017 - Oct 2017
Example TensorFlow codes and Caicloud TensorFlow as a Service dev environment.
Role in this project:
MLOps Engineer
MLOps EngineerContributions:26 commits, 16 PRs, 2 pushes in 8 months
Contributions summary:Yan primarily focused on integrating TensorFlow models within a serving environment, as evidenced by the addition of gRPC client code and modifications to the base framework for serving. They adjusted the example codes to align with TaaS 2.0 framework, emphasizing model export and evaluation. The contributions show a focus on preparing the model for production deployment and testing the serving functionality.
dev-environmenttensorflow
lienhua34/apue
May 2014 - Aug 2014
Contributions:51 commits in 3 months
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