Jérémie Dumas
Senior Research Engineer at Adobe
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolJérémie Dumas is a Senior Research Engineer in Seattle with 15 years of experience specializing in computer graphics, geometric modeling, and digital fabrication. He combines deep academic training—a PhD from Université de Lorraine and an M.Sc. from École normale supérieure de Lyon—with applied research and product-focused engineering roles at Adobe and nTopology. At Adobe he advances research-to-product pathways, and his background includes postdoctoral work at NYU and PhD research at Inria, reflecting a strong foundation in both theory and implementation. An early contributor to machine learning tooling using Theano, he has hands-on experience refactoring training loops and backend integrations for open-source projects. Outside of work he channels creativity into photography, live music, travel, and dance—interests that inform his visual and human-centered approach to graphics problems. Known for bridging rigorous research with pragmatic software engineering, he thrives on turning complex geometric ideas into usable systems.
15 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Université de LorraineMaths Physics Computer Science, Maths Physics Computer Science at Lycée ThiersMaster of Science (M.Sc.) Computer Science, Master of Science (M.Sc.) Computer Science at École normale supérieure de Lyon
English, French
Github Skills (7)
web-framework10
python10
theano10
machine-learning9
data-science8
architectures7
architecture7
Programming languages (14)
Github contributions (5)
lisa-lab/pylearn2
Feb 2011 - Apr 2011
Warning: This project does not have any current developer. See bellow.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:54 commits in 1 month
Contributions summary:Jérémie's contributions focused on refactoring and integrating a training script within a given framework. The primary task involved the creation of an example factorization process for SDA training loops. This involved adding new functionality and adapting existing features from the dense/dA.py file into the framework's utils.py file. The user's commits demonstrate an understanding of Theano and its efficient compilation for faster training.
javascripttypescript
adobe/lagrange-test-data
Dec 2020 - Apr 2022
Contributions:1 review, 4 commits, 5 PRs in 1 year 4 months
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