Weidi Xie

Machine Learning Engineer at University of Oxford

England, United Kingdom
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Summary

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Senior
🎓
Top School
Weidi Xie is a Machine Learning Engineer and research fellow in Oxford's Visual Geometry Group with a DPhil in Machine Learning and Image Analysis and a decade of experience bridging computer vision and biomedical imaging. Trained under Alison Noble and Andrew Zisserman, he has worked on cell tracking systems and publishes actively on topics spanning visual geometry and medical image analysis. His background combines rigorous academic research with practical implementation skills demonstrated across UCL and Oxford projects. Based in England, he brings deep expertise in machine learning, computer vision, and biomedical image analysis, and maintains an active scholarly presence on Google Scholar. An often overlooked strength is his telecommunications and imaging foundation from a First Class BSc and an MSc, which supports his interdisciplinary approach to imaging problems.
code10 years of coding experience
bookDoctor of Philosophy (DPhil), Machine Learning and Image Analysis, Doctor of Philosophy (DPhil), Machine Learning and Image Analysis at University of Oxford
bookBachelor of Science (BSc), Telecommunications Engineering, First Class Honour, Bachelor of Science (BSc), Telecommunications Engineering, First Class Honour at Beijing University of Posts and Telecommunications
bookUniversity College London
languagesEnglish, Chinese
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Github Skills (22)

pytorch10
python10
data-science10
machine-learning10
deep-learning10
tensorflow10
jax10
speaker-recognition9
adversarial-learning9
unsupervised-learning8
keras-tensorflow7
image-retrieval7
keras7
moving-object-detection6
object-detection5

Programming languages (3)

Jupyter NotebookMATLABPython

Github contributions (5)

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snlee81/cell_counting_v2

Jan 2017 - Feb 2017

Contributions:32 commits in 1 month
Utterance-level Aggregation For Speaker Recognition In The Wild
Contributions:26 commits, 4 PRs, 36 pushes in 1 year 9 months
speaker-recognition
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