Pierre Glaser
PhD Student at UCL
Paris, Ile-de-France
Summary
🤩
Rockstar🎓
Top SchoolPierre Glaser is a PhD student and software engineer with eight years of experience applying machine learning and statistics to clean and smart energy as well as computational neuroscience problems. He combines deep research experience at UCL, MIT and Inria with hands-on core contributions to major open-source Python projects—scikit-learn, NumPy, joblib and even CPython—improving pickling, parallelism and memory efficiency for large-array and distributed workloads. Comfortable across research and engineering, he has shipped stability and performance fixes in libraries used by millions and worked on production-facing forecasting systems for energy storage. His background in applied mathematics and HPC informs a pragmatic approach to scalable ML, from numerical stability in SGD to task parallelization and cluster orchestration. An understated strength is his knack for improving tooling and tests, turning brittle codepaths into reliable infrastructure that accelerates both research and industry workflows.
8 years of coding experience
2 years of employment as a software developer
Master Mathématiques appliquées, Master Mathématiques appliquées at ENS Paris-SaclayFrench Preparatory Class Physics Mathematics Chemistry, French Preparatory Class Physics Mathematics Chemistry at Lycée Louis Le GrandMaster's degree Applied mathematics, Master's degree Applied mathematics at Mines Paris - PSLIngénierie physique / physique appliquée, Ingénierie physique / physique appliquée at Polytechnique Montréal
French, English, German, Italian, Chinese
Github Skills (41)
caching10
memoization10
pytest10
python10
data-science10
scikit10
testing10
machine-learning10
python-multiprocessing10
data-serialization10
pickle10
numpy10
serialization10
parallel-computing10
dask10
Programming languages (12)
Github contributions (5)
cloudpipe/cloudpickle
Sep 2018 - Jun 2021
Extended pickling support for Python objects
Role in this project:
Back-end Developer
Back-end DeveloperContributions:48 reviews, 91 commits, 88 PRs in 2 years 10 months
Contributions summary:Pierre primarily contributed to enhancing cloudpickle, a Python library for extended pickling support. Their work focused on improving the handling of global variables within functions and closures, fixing bugs related to dynamic modules and their import behavior, and implementing support for pickling classes and objects with `__slots__`. These changes included modifications to core cloudpickle functions and tests, demonstrating their involvement in the project's underlying pickling mechanisms.
pythonpythonicextended
skrub-data/skrub
Mar 2018 - Jan 2019
Prepping tables for machine learning
Role in this project:Data Scientist
Data ScientistContributions:80 commits, 21 PRs, 1 push in 9 months
Contributions summary:Pierre primarily contributed to the development and implementation of machine learning models within the repository. Their work involved creating and modifying functions for ngram analysis and similarity encoding, particularly focusing on improving efficiency with NumPy implementations. Further contributions include the creation of example scripts and the enhancement of documentation for the project.
autoencoderdata-preprocessingdatadata-sciencetabular-data
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