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R&D AI Engineer | PhD candidate in Adversarial Multi-Agent Reinforcement Learning
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College of Computing - UM6P
Data Scientist
June 29, 2026 – Present
foodPicker
April 25, 2026 – Present
A minimalist Python web app to organize your daily meal programming.
View Projectytb-cc
April 24, 2024 – April 24, 2024
Generates Videos Subtitles from YouTube for English language.
View Projectstellar_website
April 17, 2024 – April 21, 2024
A simple web interface for applying a machine learning model to classify stars
View Projectstock-prediction-using-sentiment-analysis
December 27, 2023 – January 2, 2024
A real time stock market prediction application that incorporates sentiment analysis
View ProjectSVM-From-Scratch
March 27, 2023 – May 28, 2023
This repository contains implementations of multiple variant of SVM for classification task ( binary and multiclass )
View Projectcbir
January 12, 2023 – January 26, 2023
Content Based Image Retrieval system based on color, texture, and shape.
View Projectscinis-learn
December 13, 2022 – November 17, 2023
Scinis-learn is a package of non-OOP functions for Machine Learning developed by young Moroccan AI engineering students from scratch.
View Projecthambam-unconstraint-optimization
February 19, 2022 – February 19, 2022
This package contains the implementation of all the introduced algorithms in the course of unconstraint optimization for the 1st year AI engineering student at UM5-ENSIAS, with in addition, the possibility to plot the results of each optimization.
View ProjectCultural Fit Analysis
The candidate's project portfolio is heavily focused on personal, academic-style projects, which is common for entry-level candidates. The diversity of projects (ML, web apps, image retrieval) shows broad technical curiosity. However, the lack of team-based or industry-specific projects makes it difficult to assess cultural fit in a professional team environment. The target role is 'Data Scientist', and the projects align well with this domain, indicating a strong interest in the field.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's experience level is listed as 0, and the only listed 'experience' is a future role, suggesting a very junior profile. No psychometric or English test scores are available to evaluate communication, logical reasoning, or work attitude.