Xinyu Wang is a Lecturer and former Research Fellow at the Australian Institute for Machine Learning with seven years of experience in computer vision and machine learning research. Based in Adelaide, she completed a PhD in Computer Science at the University of Adelaide and transitioned from doctoral research into applied research and now academia. Her open-source contributions to the widely used OpenMMLab MMOCR toolbox include dataset converters and deployment-focused updates, reflecting practical expertise in adapting diverse document and scene-text datasets for robust recognition pipelines. She combines research rigor with hands-on engineering, enabling reproducible deployment paths for ML models—a skill valued both in research labs and production-focused teams.
6 years of coding experience
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Adelaide
OpenMMLab Text Detection, Recognition and Understanding Toolbox
Role in this project:
Back-end Developer
Contributions:266 reviews, 127 commits, 88 PRs in 10 months
Contributions summary:Xinyu's commits primarily focus on modifying and adding deprecation warnings to deployment tools within the mmocr repository. Their work involves adding deprecation messages to files related to model deployment tools to promote the use of a unified model deployment toolbox. Furthermore, the user implemented converters for datasets such as FUNSD, LV, SROIE, NAF, DeText, IMGUR, KAIST, IC11, IC13, MTWI, COCO Text v2, ReCTS, and LSVT to enhance the text recognition pipeline. The contributions demonstrate experience in adapting various datasets for use with the mmocr framework.
Contributions:26 commits, 3 PRs, 28 pushes in 2 years 9 months
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