Tom La Tour
Research Scientist at OpenAI
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolTom La Tour is a research scientist with 11 years of experience bridging machine learning, neuroimaging, and software engineering, currently based in San Francisco. He has contributed to foundational open-source tooling as a core developer on scikit-learn and conducted postdoctoral research at UC Berkeley building deep-learning-based encoding models to interpret visual and language representations in the brain. His work spans practical ML engineering—adding solvers and robustness checks to scikit-learn—to novel neuroscience methods like efficient multi-target hyperparameter search and optimal transport for individual differences. Tom holds a PhD in applied mathematics and master’s degrees from École Polytechnique and EPFL, and his publications and awards reflect a strong blend of theory and application. Early-career stints in computer vision and nanoelectronics, plus a stint leading first-responder teams in Paris, give him an uncommon mix of hands-on systems experience and discipline under pressure. He combines rigorous research instincts with production-minded code contributions, making him effective at turning complex models into reliable tools.
11 years of coding experience
7 years of employment as a software developer
Master of Science (M.Sc.), Electrical Engineering and Computer Science, Master of Science (M.Sc.), Electrical Engineering and Computer Science at Ecole polytechnique fédérale de LausanneX2010 - Master of Engineering (M.Eng.), Electrical and Electronics Engineering, X2010 - Master of Engineering (M.Eng.), Electrical and Electronics Engineering at Ecole polytechniqueDoctor of Philosophy (PhD), Applied Mathematics, Doctor of Philosophy (PhD), Applied Mathematics at Telecom ParisTech
French, English, Spanish
Stackoverflow
4,435reputation
384kreached
44answers
0questions
scikit-learn
top-1%
machine-learning
top-5%
python
top-5%
pandas
top-5%
Github Skills (23)
javascript10
python10
data-science10
scikit10
css10
machine-learning10
datasets10
linear-models10
scikit-learn10
html10
testing9
pandas9
model-optimization9
logistic-regression6
random-forest6
Programming languages (6)
Github contributions (5)
scikit-learn/scikit-learn
Apr 2015 - Dec 2022
scikit-learn: machine learning in Python
Role in this project:
Data Scientist
Data ScientistContributions:297 reviews, 126 commits, 366 PRs in 7 years 8 months
Contributions summary:Tom contributed to improving and extending the functionality of the `scikit-learn` library. Their work focused on enhancements to the `check_array` function, adding features such as dtype conversions and warning mechanisms. Further improvements involved the inclusion of new solvers, like SAG, and parameter validation in LogisticRegression, indicating expertise in model development and optimization. Their contributions also included improvements in testing procedures, showcasing a commitment to code quality and robustness within the machine learning library.
data-analysispythonstatisticsdata-sciencelearn-machine-learning
gallantlab/pycortex
Mar 2019 - Jan 2023
Pycortex is a python-based toolkit for surface visualization of fMRI data
Role in this project:Front-end Developer
Front-end DeveloperContributions:39 reviews, 76 commits, 43 PRs in 3 years 11 months
Contributions summary:Tom primarily contributed to the front-end development of a keyboard shortcut help menu within the pycortex webgl application. They added HTML elements, styled the menu using CSS, and implemented JavaScript to handle the display and functionality of the help menu. The changes included improvements to the user interface and modifications to existing JavaScript and HTML templates, enhancing user interaction and accessibility.
neuroimagingpythonfmritopological-data-analysissurface
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.