Nicolas Poilvert - Machine Learning Architect at Caption Health

Nicolas Poilvert

Machine Learning Architect at Caption Health

Denver, Colorado, United States

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Summary

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Senior

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Top School

Nicolas Poilvert is a Machine Learning Architect with 16 years of experience who blends deep academic training (PhD from MIT, engineering studies at École Polytechnique and ENS) with hands-on software engineering to build impactful ML and imaging solutions. Based in Denver, he focuses on mathematical modeling and deep learning for medical imaging and other high-impact domains such as healthcare and renewable energy. At Caption Health he drives architecture and delivery of clinical-grade ML systems, translating physics-informed models and numerical methods into production-ready software. An active contributor to scikit-image, he implemented robust array-view utilities (block_view, rolling_view) and thorough tests that improve image-data manipulation for the broader Python community. Known for bridging rigorous theory—statistical and condensed-matter physics, variational methods—with practical Python tooling (numpy, scipy, scikit-learn), he excels at turning complex models into reliable, testable components.

16 years of coding experience

Master of Science (M.Sc.), Master of Science (M.Sc.) at Ecole normale supérieure

PhD, PhD at Massachusetts Institute of Technology

Engineering Diploma, Engineering Diploma at Ecole polytechnique

French, English

Github Skills (9)

algorithm10

algorithms10

computer-vision10

python10

image-processing10

implement10

numpy10

testing9

scikit-image9

Programming languages (1)

Python

Github contributions (5)

scikit-image/scikit-image

Feb 2012 - Feb 2012

Image processing in Python

Role in this project:

Software Engineer (Focus on Image Processing & Algorithm Implementation)

Contributions:6 commits in 1 day

Contributions summary:Nicolas primarily contributed to the `scikit-image` library by implementing and testing array view functionalities. These changes introduced new methods like `block_view` and `rolling_view`, enhancing the library's ability to manipulate image data efficiently. They wrote extensive tests for the new features, ensuring their correctness and robustness. The user also refined existing code and documentation, increasing clarity and improving the user experience.

image-processingpythoncomputer-visionimage

cationly/wannier90_utilities

Feb 2010 - Oct 2010

Contributions:3 commits in 7 months

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