Yanlan Song is a software engineer based in Shanghai with 8 years of experience focused on back-end systems and AI framework engineering. She is an active contributor to OpenVINO, where she refactored and optimized core operations like atan and improved GRU/LSTM implementations through type propagation, visitor APIs, and expanded test coverage. Her work spans code, tests, and documentation, showing a pragmatic attention to maintainability and correctness in production-grade AI inference tooling. Comfortable operating in open-source ecosystems, she brings deep familiarity with numerical and graph-level operation design for model deployment. Colleagues can expect a detail-oriented engineer who pairs algorithmic insight with practical engineering refinements that improve both performance and developer ergonomics.
OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
Role in this project:
Back-end Developer
Contributions:657 reviews, 51 commits, 143 PRs in 1 year 6 months
Contributions summary:Yanlan's contributions primarily involve modifying and optimizing the "atan" (arctangent) operation within the OpenVINO toolkit. They refactored the "atan" operation by introducing a parameterized visitor API, new gtest macros, and type propagation. The user's changes also extended to the related documentation and test cases, showing expertise in both software and documentation contributions. Further contributions involve optimizing the GRU and LSTM cell/sequence implementations through the addition of typepro/visitor tests.
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.