Shanni Wu is a PhD candidate and AI-focused software engineer based in Singapore with five years of hands-on experience in computer vision and pose estimation. As an active contributor to the prominent OpenMMLab mmpose project, she has implemented multi-stage loss functions, integrated advanced backbones like RSN and MSPN, and improved multi-batch inference and post-processing including NMS options. With an MS in Artificial Intelligence from Nanyang Technological University and a strong software engineering foundation from Nanjing University of Posts and Telecommunications, she blends rigorous research training with practical system-level engineering. A national-level awardee in China's BDCI competition, she combines competitive data-science instincts with clean code and reproducible model development.
5 years of coding experience
Master of Science - MS, Artificial Intelligence, Master of Science - MS, Artificial Intelligence at 南洋理工大学
Contributions:42 reviews, 19 commits, 31 PRs in 1 year 5 months
Contributions summary:Shanni primarily contributed to the development and modification of the pose estimation model, adding features such as multi-stage loss and the integration of new backbone architectures like RSN and MSPN. They also focused on improving the post-processing steps, including the addition of a new post-process method and the integration of NMS options within the dataset implementations. Furthermore, the user has been actively refactoring and updating the codebase related to multi-batch inference and model training.
Contributions:35 commits, 33 pushes, 1 branch in 2 months
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