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Hassane AZZI

Software Development Engineer | Operations Research | Optimization | Machine Learning
French

Mobility: Île-de-France, Toulouse, Bordeaux
Activities: Software Development, Operations Research, Optimization, Machine Learning
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Hassane AZZI
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Professional Profile
Computer Science Engineer, option: Operations Research & Optimization (M2INFO_RO - 2016) from ENAC (Ecole Nationale de l'Aviation Civile), I apply my expertise in operations research, Machine Learning and software development (C++, Java, Python) to projects across various industrial sectors. My combined scientific and technical skills enable me to develop robust and optimized solutions tailored to challenges of performance, reliability, and operational efficiency.
Home Experiences Education Skills Portfolios Interests
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Experiences
  • As part of a temporary increase in activity for various projects with the Naldeo company, my role during this mission is to support different clients (Omexom, Valorem and Urbasolar) in the development of optimal management solutions for hybrid energy systems in non-interconnected zones (ZNI), in particular overseas departments and regions (Corsica, Martinique, Guadeloupe, Reunion Island and Mayotte). This advanced energy management solution is capable of maximizing the revenues of hybrid power plants, by optimizing production in real time according to the announced program, the actual state of the plant and the updating of production forecasts.
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  • For the client SCLE SFE, and within the "Reliability" team, the mission consists of developing a software application (Vcard) for simulating high-voltage substation cards.
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  • As part of the continuation of the internship carried out in Cherbourg for the E3S (Energy Smart Sailing Ship) project, this assignment involved completing the development phase of the project.
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  • Mission: As part of the E3S (Energy Smart Sailing Ship) project led by the Naval Engineering and Energy Research & Innovation Unit at SEGULA Technologies, the objective of this mission was to implement a hybrid intelligent energy management system (EMS) capable of managing the production and consumption flows of electric energy on board a long-distance cruising sailboat.

    The sailboat is equipped with renewable energy sources (solar panels, wind turbines, a hydrogenerator, a diesel generator, and a battery bank) installed on board, ensuring safety during navigation and maximum comfort for passengers (air conditioning, internet, television, shower, etc.).
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  • Project: resolution of air traffic conflicts using exact and approximate methods (metaheuristics).
    In air traffic management, separation distances must be respected to avoid any risk of collision between aircraft. Two aircraft are considered to be in conflict if the distance separating them is less than 5 nautical miles (NM) horizontally or 1,000 feet (ft) vertically. In other words, an air conflict corresponds to a loss of separation between two or more aircraft that find themselves too close to each other, in violation of predefined safety standards. The resolution of air conflicts is based on the implementation of avoidance maneuvers, such as changes in speed, altitude, or heading, in order to reestablish minimum separation distances. Each maneuver generates a cost, particularly in terms of kerosene consumption, depending on its nature. The objective of this project is precisely to minimize the total cost of maneuvers applied to aircraft, while ensuring compliance with safety standards.
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  • Airport traffic management poses many optimization challenges, making air traffic difficult to predict. In this context, assigning parking stands to aircraft, finding optimal landing sequences on one or multiple runways, as well as planning strategic taxi routes are major issues for air navigation services.The goal of this mini-project is to develop a flight sequencing strategy for arrivals at airports to avoid congestion caused by closely spaced aircraft arrivals.
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  • This project aims to develop and implement a Machine Learning algorithm able to detecting anomalies in a system, using novelty detection and outlier detection techniques.
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  • Case study and application to solve real-world industrial problems: Crew Pairing Problem (CPP), Crew Scheduling Problem (CSP), Capacitated Vehicle Routing Problem (CVRP, CVRPTW)
  • Modeling and solving optimization problems using solvers
  • Technical Environment: IBM ILOG CPLEX Optimization Studio, LocalSolver, Pyomo, Mathematical Modeling, Combinatorial Optimization, Linear Programming
Skills

Operating systems (OS)

  • Linux (Ubuntu, Debian), Windows

Programming Languages

  • Python, C/C++, Java, Rust, SQL, R, Scala

Frameworks

  • Pandas, NumPy, SciPy, PuLP, Matplotlib, Scikit-Learn, Tensorflow, PyTorch, Xgboost, MLflow
  • Spring Boot, Hibernate, STL, Boost, Qt6

Integrated Development Environments (IDE)

  • Microsoft Visual Studio, PyCharm, Eclipse, IntelliJ IDEA, Qt Creator, Visual Studio Code

Continuous integration (CI/CD) / DevOps tools

  • Git, GitLab, GitHub, Jenkins, CMake, Maven, Ansible

Software Testing and Quality (TDD, BDD)

  • SonarQube, Cucumber, CppUnit, Google Test, JUnit, Pytest

Microservices and Cloud Computing

  • Docker, Kubernetes, Kafka, API REST, FastAPI , AWS, Azure, Google Cloud Platform (GCP)

Databases (SQL and NoSQL)

  • SQL Server, MySQL, Oracle, PostgreSQL

Scientific Computing /Solvers

  • Gurobi, Cplex, Pyomo, Matlab/Simulink, GLPK, Gekko

Parallel and High-Performance Computing

  • MPI, OpenMP, CUDA

Networks, Protocols & Software Standards

  • CAN, TCP/IP, DO-178, ED-109, ED-12C

Office Tools and Scientific Writing Software

  • LaTeX, Word, Excel, PowerPoint, Outlook

Soft Skills

  • Autonomy, Communication, Leadership

Methodology

  • Agile Scrum, Kanban, SAFe methodology
Education

Applied Data Science & Machine Learning Certificate (Online)

Columbia Engineering & Emeritus Institute of Management

January 2019 to May 2019
Training in Data Science and Machine Learning:
-Data analysis and visualization;
-Use of Python Frameworks (NumPy, Pandas, Scikit-Learn, Matplotlib);
-Study of some Machine Learning algorithms: Random Forest, Text Mining, Linear Regression, Decision Trees, K-Means, SVM, Gradient Descent, Neurals Networks.
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Master's degree in Computer Science: Operations Research & Optimization (M2INFO_RO)

ENAC | ENSEEIHT | ISAE-SUPAERO | INSA | Université Toulouse III - Paul Sabatier

September 2016 to September 2018
A master's degree in Operations Research (M2RO) at ENAC (École Nationale de l'Aviation Civile) is a high-level program specializing in modeling, optimization, operations research and the solving of complex problems related to transportation, aeronautics, logistics, and other industrial sectors.

Modules & courses
Applied Mathematics · Operations Research · Optimization · Mathematical modeling · Linear programming · Combinatorial Optimization · Mathematical Programming · Graphs and networks · Optimization applications in the air transportation · Constraint programming · Optimization under uncertainty · Algorithmic complexity · Air Traffic Management (ATM) · Machine Learning Algorithms
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Languages
  • English
    Advanced
    Fluent (Level B2/C1, TOEIC 864: reading, writing and speaking)
  • French
    Expert
    Bilingual (Level C2 of the CEFR, TCF 667: Reading, writing and speaking)
  • German
    Notions
    Lower-intermediate (Level B1 of the CEFR)
Portfolios

E3S - Energy Smart Sailing Ship

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Interests

Arts

  • Chess games

Sports

  • Swimming, Jogging
Conferences and events
sep. 2021 - déc. 2022 · 1 an -

Professional Mentor for ENAC Alumni

(Volunteer)
As a member of the ENAC Alumni Association, I volunteered to support new graduates as well as current students in refining their academic or career plans.
Certifications

Mathematics for Machine Learning and Data Science (Specialization) — DeepLearning.AI

Skills: Mathematics for Machine Learning, Data Science, Linear Algebra, Calculus, Probability Theory, Statistics, Mathematical Foundations of Machine Learning, Python, NumPy, Statistical Modeling.
(View certification)

Decision Making Under Uncertainty

09/2026
Skills: Decision Analysis, Decision Theory, Decision Making Under Uncertainty, Risk Analysis, Probability Theory, Bayesian Statistics, Expected Utility Theory, Decision Trees, Monte Carlo Simulation, Sensitivity Analysis, Scenario Planning, Robust Decision Making, Value of Information, Real Options Analysis, Statistical Modeling.
(View certification)

Operations Research (3): Theory

National Taiwan University
Skills: Operations Research, Mathematical Optimization, Mathematical Modeling, Linear Programming, Integer Programming, Stochastic Optimization, Decision Theory, Network Modeling, Machine Learning, Applied Mathematics.
(View certification)

Operations Research (2): Optimization Algorithms

Skills: Operations Research, Optimization Algorithms, Linear Algebra, Algorithms, Mathematical Optimization, Combinatorial Optimization, Discrete Optimization, Linear Programming, Integer Programming.
(View certification)

Operations Research (1): Models and Applications

Skills: Operations Research, Mathematical Modeling, Model Optimization, Mathematical Optimization, Linear Programming, Integer Programming, Decision Analysis, Optimization Modeling, Applied Mathematics.
(View certification)

Discrete Optimization — Georgia Institute of Technology

Skills: Discrete Optimization, Combinatorial Optimization, Operations Research, Integer Programming, Linear Programming, Graph Theory, Algorithms, Mathematical Modeling, Computational Optimization.
(View certification)

Recherche opérationnelle : optimiser ses décisions — University of Montreal

Compétences : Recherche opérationnelle, Optimisation mathématique, Modélisation mathématique, Aide à la décision, Programmation linéaire, Programmation en nombres entiers, Analyse décisionnelle, Optimisation des systèmes.
(View certification)

Introduction to Optimization Through the Lens of Data Science (Parts 1–4) — Gurobi

Skills: Mathematical Optimization, Operations Research, Data Science, Optimization Modeling, Linear Programming, Mixed-Integer Programming, Decision Optimization, Python, Predictive Analytics, Prescriptive Analytics.
(View certification)

Mathematics for Machine Learning (Specialization) — Imperial College London

Skills: Mathematics for Machine Learning, Linear Algebra, Multivariate Calculus, Principal Component Analysis (PCA), Mathematical Modeling, Probability Theory, Optimization, Dimensionality Reduction.
(View certification)

Machine Learning Specialization — Stanford University

Skills: Machine Learning, Supervised Learning, Unsupervised Learning, Neural Networks, Decision Trees, Classification, Regression, Clustering, Model Evaluation, Python.
(View certification)

Advanced Learning Algorithms — Stanford University

Skills: Machine Learning, Neural Networks, Deep Learning, Decision Trees, Classification, Regression, TensorFlow, Model Evaluation, Bias and Variance, Python.
(View certification)

Supervised Machine Learning: Regression and Classification — Stanford University

Skills: Supervised Learning, Machine Learning, Linear Regression, Logistic Regression, Classification, Regression, Gradient Descent, Regularization, Model Evaluation, Python.
(View certification)

Machine Learning — Columbia University

Skills: Machine Learning, Statistical Learning, Supervised Learning, Unsupervised Learning, Regression, Classification, Clustering, Feature Engineering, Model Evaluation, Python.
(View certification)

Machine Learning with Python (IBM)

Skills: Machine Learning, Python, Scikit-Learn, Supervised Learning, Unsupervised Learning, Regression, Classification, Clustering, Model Evaluation, Data Preprocessing.
(View certification)

Data Visualization with Python (IBM)

Skills: Data Visualization, Python, Matplotlib, Seaborn, Pandas, Data Analysis, Statistical Visualization, Exploratory Data Analysis, Data Storytelling.
(View certification)

Data Analysis with Python (IBM)

Skills: Data Analysis, Python, Pandas, NumPy, Data Cleaning, Data Wrangling, Exploratory Data Analysis, Statistical Analysis, Data Visualization, SciPy.
(View certification)

Operations Research: An Active Learning Approach — The Hong Kong Polytechnic University

Skills: Operations Research, Mathematical Optimization, Mathematical Modeling, Linear Programming, Integer Programming, Decision Analysis, Optimization Algorithms, Problem Solving, Python.
(View certification)

Optimization: Principles and Algorithms – Linear Optimization — EPFL

Skills: Linear Optimization, Linear Programming, Mathematical Optimization, Operations Research, Convex Optimization, Optimization Algorithms, Mathematical Modeling, Duality Theory, Sensitivity Analysis.
(View certification)

Optimization: Principles and Algorithms – Network and Discrete Optimization — EPFL

Skills: Network Optimization, Discrete Optimization, Combinatorial Optimization, Graph Theory, Shortest Path Algorithms, Minimum Spanning Trees, Network Flow Optimization, Integer Programming, Operations Research.
(View certification)

Optimization: Principles and Algorithms – Unconstrained Nonlinear Optimization — EPFL

Skills: Nonlinear Optimization, Unconstrained Optimization, Mathematical Optimization, Gradient Descent, Newton's Method, Optimization Algorithms, Numerical Optimization, Mathematical Modeling, Applied Mathematics.
(View certification)

Mathematical Optimization for Business Problems

Skills: Mathematical Optimization, Operations Research, Business Optimization, Decision Analysis, Linear Programming, Integer Programming, Optimization Modeling, Resource Allocation, Prescriptive Analytics.
(View certification)

Mathematical Optimization for Engineers

Skills: Mathematical Optimization, Engineering Optimization, Operations Research, Linear Programming, Nonlinear Optimization, Mathematical Modeling, Numerical Optimization, Optimization Algorithms, Engineering Problem Solving.
(View certification)

Artificial Intelligence: Optimization Algorithms in Python

Skills: Artificial Intelligence, Optimization Algorithms, Python, Mathematical Optimization, Operations Research, Metaheuristics, Search Algorithms, Combinatorial Optimization, Algorithm Design.
(View certification)

Optimization with Python: Complete Pyomo Bootcamp A-Z

Skills: Python, Pyomo, Mathematical Optimization, Operations Research, Optimization Modeling, Linear Programming, Mixed-Integer Linear Programming, Nonlinear Programming, Solver Integration.
(View certification)

Operations Research & Optimization Projects With Python

Skills: Operations Research, Mathematical Optimization, Python, Pyomo, Linear Programming, Integer Programming, Optimization Modeling, Algorithm Design, Decision Support Systems.
(View certification)

Optimization with Python: Solve Operations Research Problems

Skills: Operations Research, Python, Mathematical Optimization, Linear Programming, Integer Programming, Optimization Modeling, Constraint Modeling, Solver Integration, Decision Optimization.
(View certification)

Pyomo Bootcamp: Python Optimization from Beginner to Advance

Skills: Pyomo, Python, Mathematical Programming, Mathematical Optimization, Linear Programming, Mixed-Integer Programming, Nonlinear Optimization, Optimization Modeling, Operations Research.
(View certification)

Introduction to Computer Science and Programming Using Python — Massachusetts Institute of Technology

Skills: Python, Computer Science, Algorithms, Computational Thinking, Problem Solving, Data Structures, Programming Fundamentals, Algorithmic Complexity, Software Development.
(View certification)

Python for Data Science

Skills: Python, Data Science, NumPy, Pandas, Data Analysis, Data Visualization, Data Manipulation, Exploratory Data Analysis, Jupyter Notebooks.
(View certification)

Linux Commands & Shell Scripting Basics

Skills: Linux, Bash, Shell Scripting, Command-Line Interface (CLI), Unix Commands, File System Management, Process Management, System Administration, Automation.
(View certification)

Software Architecture Foundations

Skills: Software Architecture, Software Design, Architectural Patterns, Design Principles, Modularity, Scalability, Maintainability, Software Engineering, System Design.
(View certification)

Coding for Everyone: C and C++ Specialization — University of California, Santa Cruz

Skills: C, C++, Programming Fundamentals, Object-Oriented Programming, Data Structures, Algorithms, Memory Management, Pointers, Problem Solving.
(View certification)

C++20 Mastery: Pure and Unfiltered — Packt Certifications Editors

Skills: C20, Modern C, C++ Standard Library, Templates, Concepts, Ranges, Lambda Expressions, Generic Programming, Object-Oriented Programming, Software Design.
(View certification)

Complete Modern C++ (C++11, C++14, C++17) — Packt Certifications Editors

Skills: Modern C++, C11, C14, C++17, STL, Smart Pointers, Move Semantics, Lambda Expressions, Templates, Generic Programming, RAII.
(View certification)

Devenir développeur C++

Compétences : C++, Programmation orientée objet, Structures de données, Algorithmes, Gestion de la mémoire, Programmation générique, STL, Débogage, Bonnes pratiques de développement logiciel.
(View certification)

Modern C++: Advanced Techniques and Features

Skills: Modern C++, Advanced C++, Templates, Metaprogramming, Move Semantics, Perfect Forwarding, RAII, Smart Pointers, STL, Generic Programming, Performance Optimization.
(View certification)

Initiation à la programmation (en C++) — EPFL

Compétences : C++, Bases de la programmation, Variables et types, Structures de contrôle, Fonctions, Tableaux, Algorithmes, Résolution de problèmes, Débogage.
(View certification)

Introduction à la programmation orientée objet (en C++) — EPFL

Compétences : C++, Programmation orientée objet, Classes et objets, Encapsulation, Héritage, Polymorphisme, Constructeurs et destructeurs, Abstraction, Conception logicielle.
(View certification)

Parallel and Concurrent Programming with C++ Part 1

Skills: C++, Parallel Programming, Concurrent Programming, Multithreading, Thread Management, Synchronization, Mutexes, Race Conditions, Performance Optimization.
(View certification)

Parallel and Concurrent Programming with C++ Part 2

Skills: C++, Concurrent Programming, Parallel Computing, Multithreading, Thread Synchronization, Atomic Operations, Thread Safety, Concurrency Patterns, Performance Optimization.
(View certification)

Test-Driven Development in C++

Skills: C++, Test-Driven Development (TDD), Unit Testing, Automated Testing, Google Test, Test Automation, Refactoring, Clean Code, Software Quality Assurance.
(View certification)

C Essential Training

Skills: C Programming, Procedural Programming, Pointers, Memory Management, Data Structures, Functions, File Handling, Debugging, Compilation.
(View certification)

Devenir développeur Java

Compétences : Java, Programmation orientée objet, Collections Java, Gestion des exceptions, Structures de données, Algorithmes, JVM, Débogage, Bonnes pratiques de développement.
(View certification)

Practical Test-Driven Development for Java Programmers

Skills: Java, Test-Driven Development (TDD), Unit Testing, JUnit, Automated Testing, Refactoring, Clean Code, Test Automation, Software Quality.
(View certification)

Advanced Python

Skills: Python, Advanced Python Programming, Object-Oriented Programming, Iterators, Generators, Decorators, Exception Handling, Modules and Packages, Python Best Practices.
(View certification)

Unit Testing and Test Driven Development in Python

Skills: Python, Unit Testing, Test-Driven Development (TDD), Pytest, Test Automation, Mocking, Code Coverage, Refactoring, Software Quality Assurance.
(View certification)