Yupan Huang is a Senior Researcher at Microsoft with nine years of experience at the intersection of NLP, multimodal learning, and large-scale pretraining. He progressed from multiple research intern roles at Microsoft Research Asia to a visiting stint at the University of Cambridge and now leads research efforts in Canada, drawing on a PhD in Computer Science from Sun Yat-sen University. Yupan contributes to prominent open-source work such as Microsoft's UniLM/layout-related projects, where he implemented decoding/evaluation improvements and helped release pretrained models including LayoutLMv3. He blends deep theoretical training with practical engineering—favoring iterative hands-on contributions over waiting for the “perfect” job—and routinely ships reproducible code and models that bridge language and visual modalities.
9 years of coding experience
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Sun Yat-sen University
Bachelor of Engineering - BE, Software Engineering, Bachelor of Engineering - BE, Software Engineering at Sun Yat-Sen University
Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
Role in this project:
ML Engineer
Contributions:7 commits, 4 PRs, 8 pushes in 1 year
Contributions summary:Yupan primarily contributed to the `layoutreader/decode_seq2seq.py` file, modifying the code to support different functionalities related to model decoding and evaluation. These changes include the release of code, uploading of a pre-trained model, and support for smaller data sizes. The user also released layoutlmv3 and removed an unused function from `rcnn_vl.py`.
Contributions:2 commits, 6 pushes, 1 branch in 3 years 3 months
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