Industrial Engineering graduate from École Centrale Casablanca, with an exchange period at École CentraleSupélec in optimization, AI, and multi-agent systems.

My core field is operations, logistics, and supply chain, approached with quantitative methods: modeling, discrete-event simulation, optimization, and data analysis.

I use ML and deep learning when useful for the decision problem, and I work with explicit assumptions, reproducible analysis, and outputs that operators and decision-makers can use.

EDUCATION

École Centrale Casablanca

Sep 2022 - Sep 2025

Engineering Degree - Industrial Engineering (Graduated Sep 2025)

  • Operations research and optimization: mathematical programming, metaheuristics, combinatorial and stochastic optimization
  • Supply chain and logistics: flow optimization, distribution network modeling, demand planning
  • Industrial simulation: production system modeling, digital twins, smart factory, discrete event simulation
  • Data science and machine learning: predictive analytics, computer vision, deep learning, reinforcement learning
  • Management and continuous improvement: Lean Manufacturing, Six Sigma, ERP systems

École CentraleSupélec

Feb 2024 - Jun 2024

Engineering Exchange Program

  • Optimization and flow management in complex systems
  • Optimization and control of multi-agent dynamic systems
  • Artificial intelligence and reinforcement learning
  • Collaborative robotic systems and human-machine synchronization
ArabicNative
FrenchC1 - Professional (TOEIC 965)
EnglishC1 - Professional
PROFESSIONAL EXPERIENCE

SAPRESS Logistics / UM6P (MILEX Project)

Mar 2025 - Aug 2025

Casablanca, Morocco

Final-Year Research Internship (PFE)

  • Context: Field study and diagnostic: discussions and on-site visits at the SAPRESS SLM Casablanca agency to understand operational processes, identify bottlenecks, and formalize real routing constraints
  • What I did: Mathematical modeling: design and implementation of a hybrid optimization engine combining mathematical programming (OR) and metaheuristics for multi-point vehicle routing with real-time traffic management
  • Methods/Tools: Machine learning: development of a Graph Neural Network (GNN) for traffic pattern prediction from GPS data, integrated into the routing system to improve solution quality
  • Output: Full TMS prototype: integration of all work into a complete Transport Management System (TMS) enabling route planning and real-time re-optimization with operator interface
Python
Gurobi
PyTorch
OR-Tools
PyTorch Geometric

Newrest

Oct 2024 - Feb 2025

Supply chain analysis project

  • Context: Cold storage warehouse optimization (-18 degrees C)
  • What I did: Analyzed logistical flows in cold/negative storage to identify inefficiencies and dependencies
  • Methods/Tools: Industrial benchmarking and recommendations for cold storage automation
  • Output: Developed optimized system model balancing space utilization, reduced human intervention, and energy efficiency
  • Output: Defined KPIs and drafted a master plan for the transition
Python
SQL

Air Liquide

Feb 2024 - Apr 2024

Hydrogen supply chain optimization project

  • Context: Gaseous hydrogen multi-site supply chain modeling using Simul8: filling centers, trailer fleets, client station networks with variable consumption patterns
  • What I did: Dynamic resource allocation algorithm integrating operational constraints (driver shifts, travel times, inventory levels)
  • Methods/Tools: Monitoring of key metrics: Service Level and Lead Time
  • Output: Comparative study of alternative configurations and strategic recommendations for optimal system dimensioning
Simul8
Python

Institut NeuroPSI (CentraleSupélec)

Feb 2024 - Jun 2024

Haptic feedback prosthetic arm development

  • Context: Integrated strain gauges and optimized haptic feedback for collision and deformation detection
  • What I did: Haptic feedback surpasses purely vision-based approaches
  • Methods/Tools: Designed predictive model for 2D hand localization based on deformations, with planned 3D extension
Python
scikit-learn
ACADEMIC / RESEARCH PROJECTS

Academic and research projects completed during the engineering curriculum.

Digital Twin & Simulation

Smart Factory Digital Twin

Jan 2025

  • Digital twin of assembly line in FlexSim (production stations, conveyors, AGVs, cobots), in collaboration with École Centrale Lyon / Centrale Lille
  • Bidirectional FlexSim-Node-RED communication via SQLite for real-time data collection and interactive dashboard visualization
  • Virtual camera quality control system with automatic defective part reinjection
FlexSim
Node-RED
SQLite

Multi-Agent Systems & Reinforcement Learning

Drone Coordination (CentraleSupélec)

Apr 2024 - Jun 2024

  • Multi-Agent Reinforcement Learning (MARL) strategies for decentralized drone coordination (Leader-Follower, Virtual Structure topologies)
  • Policy gradient methods for cooperative multi-agent systems with communication constraints
  • Strategies for threat evasion and optimal formation recovery in complex missions
  • Python simulation environment with quantitative performance metrics for trajectory tracking and energy efficiency
Python
MATLAB

Computer Vision & Deep Learning

Vision Transformers for Medical Image Segmentation (COVID-19)

Oct 2023 - Feb 2024

  • Self-supervised three-phase pipeline: 3D GAN to synthesize pseudo lung masks by subtracting generated healthy images, then lesion segmentation by TransUNet
  • Integrated Vision Transformers into U-Net architectures to capture long-range spatial dependencies in 3D medical imaging
  • No manual pixel-level annotations required
  • Dice Score 50.09% -> 72.89%, sensitivity 98.52%, specificity 99.99%
  • Specialized loss functions: Enhanced Contrastive Loss, Sensitivity Enhanced Loss
PyTorch
CUDA
TransUNet
Vision Transformers
3D GAN

Optimization & Planning

Task Assignment Automation & Line Balancing

Jan 2024 - Ongoing

  • Line balancing optimization for textile production lines
  • Planning tool for workstation assignment, reduction of bottlenecks and improvement of operational efficiency
  • Integration of Large Language Models (LLM) to automate machine assignment based on client constraints
Python
Gurobi

Semiconductor R&D

Metal-Semiconductor Junctions & FETs (C2N & GeePs Labs)

Jun 2024

  • Fabrication and characterization of MOSFETs through lithography on pure silicon
  • Characterization of capacitances and NPN transistors under varying voltage conditions
  • Simulation and performance optimization of NMOS (100nm gate oxide) using ECORCE
  • Research on RibbonFET and its applications in advanced electronics
ECORCE
TECHNICAL SKILLS

Optimization / Operations Research

Mathematical programming
Metaheuristics
Combinatorial optimization
Stochastic optimization
Gurobi
OR-Tools

AI / Machine Learning

PyTorch
TensorFlow
scikit-learn
GNNs (PyTorch Geometric)
Vision Transformers
Reinforcement learning
MARL
NLP / LLMs

Data & Visualization

Python
SQL
Pandas
NumPy
SciPy
Matplotlib
Plotly
Power BI
ENGINEERING SKILLS

Simulation / Digital Twin

Discrete event simulation
Simul8
FlexSim
Simulink
Node-RED integration

Engineering Tooling

MATLAB
Git
Docker
FastAPI
Jupyter
REST API
SolidWorks

Industrial Methods

Lean Manufacturing
Six Sigma
ERP systems
KPI definition
Scrum
CERTIFICATIONS
RESEARCH <-> ENGINEERING
  • My profile sits between engineering execution and research framing: I work with operational constraints, heterogeneous data, and deployable decision support, while staying interested in representation learning and frugal, industry-usable AI systems.
  • Operations research and optimization applied to logistics; ML and neural networks for optimization and process improvement; deep learning for resource allocation and dynamic control.
TECHNICAL SKILLS
PYTHON
PYTORCH
GUROBI
SIMUL8
FLEXSIM
SQL
TENSORFLOW
SCIKIT-LEARN