Freelancer profile translated to English.
Back to original languageAbout Hassane
Profile
Backend C++ developer, specialized in optimization, operations research, and machine learning. I design and implement high-performance algorithms to solve complex industrial problems and develop robust software applications. For more details on my professional background and projects, I invite you to consult my LinkedIn profile.
💻 Key Skills
1) Optimization & Operations Research
- Modeling and solving of concrete industrial optimization and operations research problems
- Use of approximate methods (heuristics and metaheuristics) to solve large-scale problems.
- Implementation of optimization algorithms in Python, C++, and Java.
- **Example methods used**: Simulated Annealing, Decomposition Methods, Genetic Algorithms, Constraint Programming, Column Generation, Branch-and-Bound, Dynamic Programming, Integer Linear Programming.
2) Software Development
- Analysis of needs and requirements for a software solution
- Backend software design and development in C++ and Java under Linux and Windows
- Unit testing of components and modules of a computer application
- Deployment, corrective, and evolutionary maintenance of the software solution.
3) Machine Learning
- Supervised and unsupervised learning: modeling and training of adapted models.
- Data processing and preparation for model training and evaluation.
- Integration of algorithms into production systems.
- Design and implementation of Machine Learning algorithms with the Scikit-learn Framework
English
Fluent
French
Native or bilingual
German
Conversational
Can work on-site
Paris (up to 50km), Bordeaux (up to 50km), Nantes (up to 50km), Lyon (up to 50km), Toulouse (up to 50km)
Experience
- Naldeo Digital for ClimateOptimization & Machine Learning EngineerENERGY AND UTILITIESMay 2024 - Today (2 years and 1 month)Bayonne, FranceAs part of a temporary increase in activity for various projects with Naldeo, my role during this assignment is to support different clients (Omexom, Valorem, and Urbasolar) in the development of optimal control solutions for hybrid energy systems in non-interconnected zones (ZNI), particularly in overseas departments and regions (Corsica, Martinique, Guadeloupe, Guiana, Reunion, and Mayotte). This advanced energy management solution is capable of maximizing the revenue of hybrid power plants by optimizing real-time production based on the announced schedule, the actual state of the plant, and updated production forecasts.-Sizing and performance evaluation studies of hybrid power plants;-Development and supply of an EMS ENERBIRD software system (optimization, control, and energy monitoring) for several hybrid renewable energy (wind and photovoltaic) production plants, including battery storage;-Implementation of optimization and operations research algorithms (MILP, MINLP, genetic algorithms) to control renewable energy production and storage plants;-Development of a Machine Learning predictive model capable of more accurately estimating electrical energy production over a 24-hour horizon;-Design of energy simulators and management of commissioning and acceptance testing phases;-Participation in defining the technological development roadmap.Technical Environment: Python, Visual Studio Code, Machine Learning (neural networks), Scikit-Learn, PyCharm, MLflow, GitLab, Matlab/ Simulink, optimization tools (PuLP, Gekko), Model Predictive Control (MPC), SCADA
- SCLE SFEBack-End C++ Developer | Software Development EngineerENERGY AND UTILITIESMarch 2022 - April 2024 (2 years and 1 month)Toulouse, FranceCONTEXTFor SCLE SFE client and within the "Reliability" team, this assignment involves developing software (Vcard) to simulate high-voltage electrical substations cards.ACTIVITIES
- Modification and restructuring of the software architecture (adding new features);
- Development of a GUI in Qt5 under Linux (Virtual Machine) to manage cards via a CAN interface and also allows the user to control the outputs of each card;
- Bug fixing and execution of unit and integration tests for the GUI;
- Writing project documents and deliverables;
- Corrective and evolutionary maintenance of Vcard
Technical EnvironmentC/C++17, Linux (Ubuntu, Debian), Qt5, Python (PyCharm), Shell script/ Bash, GitLab, Jenkins, CAN. - Segula TechnologiesC++/Java Development Engineer | Software Engineer C++/Java (Freelance)ENERGY AND UTILITIESDecember 2018 - February 2022 (3 years and 2 months)Brest, FranceCONTEXTContinuing the E3S project developed in Cherbourg, this assignment focuses on the software development of the electrical energy management system aboard a sailboat.ACTIVITIES
- Design and development of a software system (EMS) composed of several layers, primarily using microservices with Spring Boot;
- Implementation of a real-time application (REST API) in Java to automatically collect weather data via devices (TCP/IP) connected to the system;
- Coding and writing of unit and integration tests for the application's components and modules using JUnit and Mockito;
- Implementation of the optimization algorithm in C++ to manage electrical energy production and consumption flows.
Technical Environment & keywordsC++17, Java 11, Python, Spring Boot, Spring Data, Microservices, Microsoft Visual Studio Code, Bitbucket, Git, Jenkins, Maven, SonarQube, Kafka, TCP/IP, MySQL, Maven, REST API, JUnit, Mockito, Shell Script, Real-time system, optimization, Human-Machine Interaction, Clean Code, Multithreading
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Education
- Master informatique, parcours: Recherche opérationnelle & optimisation (M2INFO_RO)ENAC | ISAE-SUPAERO | Université Toulouse III - Paul Sabatier2018Applied Mathematics · Operations Research · Optimization · Mathematical modeling · Linear & Mixed Integer 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. URL: https://www.univ-tlse3.fr/decouvrir-nos-diplomes/master-parcours-recherche-operationnelle-optimisation-ro
- Applied Data Science (5-month online certification program)Columbia Engineering & Emeritus Institute of Management2019-Training in Data Science and Machine Learning -Data analysis and visualization -Use of Python frameworks (NumPy, Pandas, Scikit-learn, Matplotlib) -Study of various machine learning algorithms: Random Forest, Text Mining, Linear Regression, Decision Trees, K-Means, SVM, Gradient Descent, Neural Networks Certificate: https://www.smartcertificate.com/SmartDiploma/Default.aspx?iZrsRKuPtTPnMoPxa4vUY0j8EUyneZnub9MwrFidmpYKlnoV26oP%2fjxQrWvj08k5#/
Certifications
- Mathematics for Machine LearningImperial College London2025
- Discrete OptimizationGeorgia Institute of Technology2025