Mostefa Naceur
R&D Machine Learning Engineer at NGTV Experience
France
Summary
👤
Senior🎓
Top SchoolMostefa Naceur is an R&D Machine Learning Engineer based in France with a Ph.D. in Artificial Intelligence and nine years of experience bridging academic research and industry. He has progressed from a doctoral candidate and postdoctoral researcher to his current role at NGTV Experience, applying advanced ML techniques to product-focused R&D. Skilled in programming, mathematics, and machine learning, he combines theoretical depth with practical implementation across research and engineering teams. His background includes a strong publication and research training environment at LIGM and ESIEE Paris, complemented by professional development at ESCP. Notably, he transitions complex AI concepts into deployable solutions, reflecting a pattern of moving research prototypes toward real-world impact. He brings a curious, methodical approach to problem solving, often blending rigorous analysis with hands-on system development.
9 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy (PhD), Doctor of Philosophy (PhD) at University of Paris-Est, ESIEE Paris, LIGM LabMaster's degree, Master's degree at University of BiskraCertificate, Certificate at Institute ISEFRE, ESCP Europe
Arabic, French, English, Spanish
Github Skills (11)
convolutional-neural-networks8
classify8
classification7
keras6
imagenet6
python5
deep-learning5
machine-learning5
image-classification4
tensorflow4
deep-neural-networks3
Programming languages (2)
Github contributions (5)
MostefaBen/Trash-classification
May 2019 - Feb 2022
Building a Smart System based on Deep Convolutional Neural Networks to classify Trash (Python implementation)
Contributions:20 commits, 1 PR, 20 pushes in 2 years 9 months
imagenetpythondeep-learningpython-implementationconvolutional-neural-network
MostefaBen/Fully-automatic-brain-tumor-segmentation-with-deep-learning-based-selective-attention
Dec 2019 - May 2020
Keras implementation of the paper "Fully automatic brain tumor segmentation with deep learning-based selective attention using overlapping patches and multi-class weighted cross-entropy", by Mostefa Ben naceur et al. (Medical Image Analysis)
Contributions:49 commits, 4 PRs, 55 pushes in 5 months
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