Simon P
Professeur Adjoint at Le ministère de la Défense nationale
Montreal, Quebec, Canada
Summary
🤩
Rockstar🎓
Top SchoolSimon P is an education technology professor and research-oriented leader based in Montreal with a decade of experience bridging academic administration, teaching, and technical engineering. Currently serving as Adjoint à la doyenne at Université de Montréal and professeur associé at Université Laval, he combines policy and program leadership with hands-on course delivery and student success advising. His technical background includes backend development and CI/CD automation for influential open-source deep learning projects such as Theano and DeepLearningTutorials, where he contributed GPU backend work, testing, and build infrastructure improvements. That uncommon blend of rigorous doctoral-level research, operational stewardship in higher education, and practical engineering expertise enables him to translate complex machine-learning tooling into reliable, testable workflows for teaching and research. Colleagues value him for steady program coordination across journals and research hubs and for bringing reproducible engineering practices into academic contexts.
10 years of coding experience
Maîtrise (M. Sc.) Intelligence et transformation, Maîtrise (M. Sc.) Intelligence et transformation at Université LavalDoctorat (Ph. D.) Sciences de l'éducation (psychopédagogie), Doctorat (Ph. D.) Sciences de l'éducation (psychopédagogie) at Université de MontréalAEC Coordination d'événements et de congrès, AEC Coordination d'événements et de congrès at Institut de tourisme et d'hôtellerie du Québec
German, Spanish, English, French
Github Skills (20)
python10
testing10
git-repository10
bash10
cicd10
build-automation10
jenkins10
jenkins-ci10
github-repos10
theano10
dft9
dockers9
gpu-programming9
docker9
fft9
Programming languages (8)
Github contributions (5)
Theano/Theano
Apr 2016 - Apr 2018
Theano was a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It is being continued as PyTensor: www.github.com/pymc-devs/pytensor
Role in this project:
Back-end Developer & Test Automation Engineer
Back-end Developer & Test Automation EngineerContributions:191 commits, 131 PRs, 25 pushes in 2 years
Contributions summary:Simon primarily contributed to the Theano library by modifying and adding tests for the `function.copy` functionality, specifically related to handling unused inputs and updates when copying functions. They implemented tests to ensure the correct behavior of function copies with and without updates. Furthermore, the user made changes related to the new GPU backend, transitioning code from the `sandbox` to the main Theano directory and porting and testing FFT functionality.
mathematical-expressionsmultidimensional-arrayspymcpythontheano
lisa-lab/DeepLearningTutorials
Aug 2016 - Mar 2018
Deep Learning Tutorial notes and code. See the wiki for more info.
Role in this project:DevOps Engineer & Automation Engineer
DevOps Engineer & Automation EngineerContributions:19 commits, 17 PRs, 3 pushes in 1 year 6 months
Contributions summary:Simon primarily focused on setting up and enhancing the CI/CD pipeline for the project. They implemented a Jenkins buildbot script, added test suite names, and integrated JUnit reporting for performance tests. The user also improved the build process by installing libgpuarray and including explicit CUDA paths, thereby ensuring automated builds and testing capabilities within the deep learning environment.
deep-learning
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