Wenqi Li
Senior Applied Research Scientist at NVIDIA
London, England, United Kingdom
Summary
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Rockstar🎓
Top SchoolWenqi Li is a Senior Applied Research Scientist based in London with 13 years of experience applying computer vision and pattern recognition to medical image analysis. With a PhD from the University of Dundee and a track record at institutions like UCL, King’s College and NVIDIA, Wenqi focuses on 3-D texture analysis, segmentation, and ML-driven image classification for healthcare. They are an active open-source contributor to MONAI and related medical imaging toolkits, improving tutorials, model integration, and deployment compatibility across versions. Wenqi’s work blends deep research rigor with practical engineering—adding features like channel-first support and TensorBoard integration—helping bridge research prototypes to robust, production-ready imaging pipelines.
13 years of coding experience
3 years of employment as a software developer
Exchange student, Exchange student at The University of DundeeMaster of Science (M.Sc.) with distinction, Master of Science (M.Sc.) with distinction at University of DundeeBachelor's degree, Bachelor's degree at University of Science and Technology Beijing
Chinese, English
Stackoverflow
153reputation
2kreached
13answers
0questions
Github Skills (22)
pytorch10
convolutional-neural-networks10
python10
image-processing10
machine-learning10
deep-learning10
tensorflow10
ai10
neural-network10
medical-imaging10
computer-vision10
jupyter-notebook10
unit-testing9
segmentation9
image-segmentation9
Programming languages (7)
Github contributions (5)
NifTK/NiftyNet
Mar 2017 - Mar 2020
[unmaintained] An open-source convolutional neural networks platform for research in medical image analysis and image-guided therapy
Role in this project:
ML Engineer
ML EngineerContributions:3 releases, 1643 commits, 169 PRs in 2 years 11 months
Contributions summary:Wenqi implemented residual units, downsample/upsample blocks in Python. They modified tests for the upsample and residual block, including tests for 3D shape and other input shapes. The user's commits are in the medical imaging domain, with a focus on open-source convolutional neural networks platform for research.
image-analysistherapymedical-imagedeep-learningconvolutional
Project-MONAI/MONAI
Jan 2020 - Jan 2023
AI Toolkit for Healthcare Imaging
Role in this project:ML Engineer
ML EngineerContributions:16 releases, 2971 reviews, 745 commits in 3 years
Contributions summary:Wenqi Li's commits to the MONAI repository primarily involve the implementation of new features and improvements related to model training and analysis within the context of healthcare imaging. Their contributions span a range of areas, including the integration of the `torch.utils.tensorboard` library for visualising image data and losses and the addition of new features such as "channel first" for images and "no channel" to reader. They have also been involved in improving the functionality of the deep learning models.
pytorchpythondeep-learningmedical-image-processingcomputer-vision
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