Mohamed Bouhlel
Postdoctoral Researcher at University of Michigan
Ann Arbor, Michigan, France
Summary
👤
Senior🎓
Top SchoolMohamed Bouhlel is a Postdoctoral Researcher with a PhD in Applied Mathematics and a decade of experience translating advanced mathematical methods into practical data-science and optimization tools. He specializes in surrogate modeling, high-dimensional optimization, uncertainty quantification, and machine learning, and has strong software skills in Python, R, Matlab and scientific computing languages. His doctoral work produced KPLS and the SEGOKPLS algorithm for constrained, high-dimensional optimization, validated on industrial blade design at SNECMA, and he continues to impact practice as a contributor and documentation lead for the open-source Surrogate Modeling Toolbox (SMT). Based in Ann Arbor, Mohamed blends academic rigor with product-focused development—evidenced by his optimization work for the Webfoil airfoil design tool—and is known for clear documentation that helps users adopt complex modeling toolchains.
9 years of coding experience
4 years of employment as a software developer
Master's degree, Applied Mathematics, Statistics, Scientific programming, Master's degree, Applied Mathematics, Statistics, Scientific programming at Université Paul Sabatier Toulouse IIIBachelor's degree, Mathematics and Computer Science, Bachelor's degree, Mathematics and Computer Science at Université Nice Sophia AntipolisEngineer's degree, Applied Mathematics and Modelisation, Engineer's degree, Applied Mathematics and Modelisation at Institut national des Sciences appliquées de ToulouseDoctor of Philosophy - PhD, Applied Mathematics, Doctor of Philosophy - PhD, Applied Mathematics at ISAE-SUPAERO
English, French, Arabic
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (3)
documentation10
jupyter-notebook9
python7
Programming languages (2)
Github contributions (5)
SMTorg/smt
Nov 2016 - Apr 2020
Surrogate Modeling Toolbox
Role in this project:
Technical Writer
Technical WriterContributions:3 releases, 306 commits, 124 PRs in 3 years 5 months
Contributions summary:Mohamed's commits primarily involve documenting the codebase, as evidenced by the frequent commit messages "Doc" and changes focusing on example files. The user updated the setup.py file, likely in relation to the build/installation process. The user's work also involved starting a Jupyter notebook and other documentation fixes, showing a focus on user-facing documentation.
multi-fidelitytoolboxmachine-learningdensity-estimationsurrogate-models
bouhlelma/smt
Dec 2017 - Jan 2018
Contributions:15 pushes in 21 days
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