Fabian Pedregosa
Research Scientist at Google DeepMind
Geneva, Geneva, Switzerland
Summary
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Rockstar🎓
Top SchoolFabian Pedregosa is a research scientist at Google DeepMind with 19 years of experience at the intersection of optimization, numerical linear algebra, and machine learning. He holds a PhD in Computer Science and a strong academic pedigree including postdocs at ENS and UC Berkeley, and his doctoral work focused on feature extraction and supervised learning for fMRI. Fabian is a prolific open-source contributor to flagship projects such as scikit-learn, SciPy, JAXopt and nilearn, improving numerical stability, performance of linear algebra routines, and ML tooling used by researchers worldwide. His contributions show a rare blend of theory and practice—from refactoring BLAS/LAPACK code and stabilizing line-search algorithms to prototyping defenses against membership inference and reproducing research with Colab notebooks. Based in Geneva, he combines deep mathematical insight with production-grade engineering, often surfacing subtle numerical issues and fixing them at the library level. Colleagues value him for making complex optimization methods robust and widely usable across both neuroimaging and general ML ecosystems.
19 years of coding experience
5 years of employment as a software developer
Ecole EuropeeneMaster's degree, Mathematics, Master's degree, Mathematics at Universidad de GranadaDoctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at Université Pierre et Marie Curie (Paris VI)IES Padre Manjon, Granada
Spanish, French, English
Stackoverflow
6,399reputation
667kreached
34answers
1question
memory-management
top-1%
profiling
top-1%
python
top-1%
Github Skills (59)
algorithm10
algorithms10
numerical10
python10
data-science10
brain-imaging10
testing10
scikit10
memory-management10
machine-learning10
blas10
flax10
numpy10
linear-models10
regression10
Programming languages (13)
Github contributions (5)
pythonprofilers/memory_profiler
Dec 2011 - Nov 2022
Monitor Memory usage of Python code
Role in this project:
Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:5 reviews, 354 commits, 80 PRs in 11 years
Contributions summary:Fabian primarily contributed to the memory_profiler project by implementing features, fixing bugs, and improving the codebase. They worked on porting the tool to OSX, fixing build and release issues, and enhanced the output formatting. Furthermore, they added IPython magics and introduced various backends to support different memory usage tracking methodologies. The user's contributions involved both code modifications and documentation updates, indicating a strong understanding of the project's goals and functionality.
python
scikit-learn-contrib/lightning
Sep 2015 - Jun 2021
Large-scale linear classification, regression and ranking in Python
Role in this project:Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:164 commits, 62 PRs, 88 pushes in 5 years 10 months
Contributions summary:Fabian contributed to Python 3 compatibility fixes and addressed issues related to sparse samples in the Stochastic Average Gradient (SAG) algorithm. They modified code within the `lightning/impl` directory, particularly in files associated with machine learning algorithms like Newton's method and FISTA. The user also added tests to verify the functionality of the implemented algorithms. The contributions demonstrate a focus on improving the library's robustness and compatibility for machine learning tasks.
classificationpythonmachine-learning
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