Rodrigo Benenson
Senior Research Scientist at Google
Zurich, Zurich, Switzerland
Summary
👤
Senior🎓
Top SchoolRodrigo Benenson is a Senior Research Scientist in Zurich with 16 years of experience at the intersection of robotics, perception, and machine learning, currently leading research efforts at Google. He holds a PhD in Robotics and has a strong track record translating academic advances into practical systems—from driverless-vehicle prototypes during his PhD and postdoc work to production-grade research at Max-Planck and Google. Rodrigo is an experienced open-source contributor, improving Python bindings and usability across prominent projects like Halide, Keras, and the Assimp asset importer, which reflects his fluency across Python and C++ stacks. Known for pragmatic engineering, he combines deep theoretical knowledge with hands-on API and tooling improvements that make research more reproducible and widely usable. An understated detail: his contributions often target developer ergonomics (callbacks, bindings and tutorials), showing a consistent focus on making complex systems accessible to others.
16 years of coding experience
1 year of employment as a software developer
Alliance Française de ValparaisoPhD, Robotics, PhD, Robotics at Ecole Nationale Supérieur des Mines de ParisEngineer, Electronics, Engineer, Electronics at Universidad Tecnica Federico Santa Maria
English, French, Spanish, German
Stackoverflow
2,911reputation
1.7mreached
24answers
21questions
pdf
top-5%
merge
top-5%
command-line-interface
top-5%
Github Skills (38)
c-language10
python10
image-processing10
machine-learning10
assimp10
numpy10
keras10
deep-learning10
tensorflow10
cplus10
neural-network10
cpp10
cprogramming-language10
command-line-interface9
apidoc9
Programming languages (15)
Github contributions (5)
halide/Halide
Dec 2014 - Aug 2015
a language for fast, portable data-parallel computation
Role in this project:
Back-end Developer
Back-end DeveloperContributions:151 commits, 3 PRs, 48 comments in 8 months
Contributions summary:Rodrigo primarily focused on enhancing the Python bindings for the Halide library, aiming to improve support for various features. They implemented several methods and classes for the API, specifically concerning `Expr`, `Var`, `Func`, `Image`, `RDom`, `Argument`, and `Target` to provide a comprehensive python interface. Furthermore, they addressed issues related to the operators and type conversion for the new bindings, while ensuring that the tutorial examples and example apps still function properly. The user's commits involved the restructuring of source files and adjusting the internal logic of the library to support the intended functionality.
computationhexagonhalideparallelgpu
keras-team/keras
Sep 2015 - Sep 2015
Deep Learning for humans
Role in this project:ML Engineer
ML EngineerContributions:6 commits, 5 PRs, 24 comments in 15 days
Contributions summary:Rodrigo contributed to the Keras library by addressing specific issues and making improvements to the code. They fixed an import for Python 3 compatibility, enhancing the library's cross-version compatibility. Furthermore, the user modified the `Progbar` utility and the `BaseLogger` callback to enhance flexibility and provide a more informative user experience during model training, demonstrating an understanding of the library's inner workings and user-facing components. The updates to the callbacks improved output formatting.
pythondata-sciencedeep-learningneural-networksmachine-learning
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