Justin Pinkney
Senior Machine Learning Researcher at Midjourney
Cambridge, England, United Kingdom
Summary
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Rockstar🎓
Top SchoolJustin Pinkney is a Senior Machine Learning Researcher with 13 years of experience bridging deep learning, computer vision, and applied physics. Based in Cambridge, he has driven research and product-focused ML work at Midjourney and Lambda after a consultancy career solving industrial imaging and instrumentation challenges at Sagentia and MathWorks. He contributes to high-profile open-source projects such as extending image-variation capabilities in a stable-diffusion implementation and improving test coverage in scikit-image, reflecting both production-grade model engineering and rigorous QA. Trained as a physicist with a PhD in Biophysics from Oxford, he combines strong theoretical grounding with practical skills in Python, OpenCV, and model deployment to turn research ideas into reliable tools. Notably, his background in building custom fluorescence instruments and microscopy algorithms gives him a unique edge in imaging-driven ML applications.
13 years of coding experience
2 years of employment as a software developer
MPhys, Physics, 1st Class (Hons), MPhys, Physics, 1st Class (Hons) at University of Oxford
Japanese
Github Skills (12)
computer-vision10
pytorch10
machine-learning10
gradio10
stable-diffusion10
scikit-image10
python10
image-processing10
numpy10
test-automation10
pytest9
py9
Programming languages (8)
Github contributions (5)
justinpinkney/stable-diffusion
Sep 2022 - Jan 2023
Role in this project:
ML Engineer
ML EngineerContributions:60 commits, 13 PRs, 51 pushes in 4 months
Contributions summary:Justin implemented image variation functionality, including the addition of image variations and related features like updating the README file. These changes incorporated new scripts such as `image_variations.py` and `gradio_variations.py`. The code modifications involve loading and processing images for model input, defining sampling functions using DDIM and PLMS samplers, and enabling interactive image generation through a Gradio interface, demonstrating a focus on extending and improving the stable diffusion model capabilities.
scikit-image/scikit-image
Apr 2017 - Sep 2018
Image processing in Python
Role in this project:QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:11 commits, 1 PR, 4 comments in 1 year 4 months
Contributions summary:Justin's commits primarily involve testing and improving the `gray2rgb` function in the `scikit-image` library. Their work includes writing and refining test cases to ensure correct behavior, particularly for 1-dimensional image inputs. They focused on both functionality and accuracy, simplifying test assertions and correcting the output format of the `gray2rgb` function. The user's contributions highlight a dedication to ensuring the reliability and correctness of image processing functionality.
image-processingpythoncomputer-visionimage
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