Junde Wu
United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolJunde Wu is an AI researcher, builder, and founder focused on healthcare-grade machine learning, holding a PhD from Oxford and over nine years in AI with five years dedicated to clinical applications. He co-founded Baidu Healthcare Group, led development of an FDA Class III–certified AI medical device for eye screening, and earned industry recognition including an AAAI Most Influential Paper and CVPR Best Paper nomination. As founder of Panoptes Group he built a checkout-free grocery vision system that was acquired by SenseTime and later commercialized into million-dollar deployments, and he now leads the Super Medical Intelligence Lab with active open-source work such as MedSegDiff—advancing diffusion-based medical image segmentation. His portfolio blends deep research (40+ papers, 1,300+ citations) with product delivery, clinical validation, and commercialization, evidencing a rare ability to move models from publication to regulated, revenue-generating systems. Based in the UK, he pairs hands-on ML engineering with strategic leadership across startups, large tech, and finance consulting.
8 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, AI for Healthcare, Large Language Model, Computer Vision, Doctor of Philosophy - PhD, AI for Healthcare, Large Language Model, Computer Vision at University of OxfordBachelor's degree, Mechatronics, Robotics, and Automation Engineering, Bachelor's degree, Mechatronics, Robotics, and Automation Engineering at Harbin Institute of Technology
Github Skills (8)
medical-imaging10
pytorch10
machine-learning10
image-segmentation10
deep-learning10
segmentation10
python10
numpy9
Programming languages (4)
Github contributions (5)
ImprintLab/MedSegDiff
Dec 2022 - Mar 2023
Using Diffusion Models to Segment/Reconstruct Organs from Medical Images [AAAI Most influential Paper]
Role in this project:
ML Engineer
ML EngineerContributions:1 review, 44 commits, 10 PRs in 3 months
Contributions summary:Junde contributed to the development of medical image segmentation using a diffusion model. They created utility functions, updated existing diffusion model components, and integrated DPM solver. These contributions indicate a focus on implementing core functionalities and optimizing existing modules related to the diffusion model architecture. Their work included modifications to the unet and segmentation sampling scripts, further suggesting an involvement in model training, sampling and inference.
diffusion-modelsartificial-intelligencedeep-learningdenoising-diffusionimage-segmentation
WuJunde/wujunde.github.io
Jun 2019 - Nov 2025
Contributions:48 pushes, 2 branches in 6 years 6 months
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