Benjamin Uwizeye

Key Contributions:

• Development of libraries in Java and C# to extract accounts credentials via SOAP from an online secure CyberArk vault, enabling identity processing batches to access LDAP servers and databases
• Configuration and development of SailPoint connectors.
• Development of the integration connector between the Smart Traffik application and SailPoint.

Environment & Tools: Java, C#, .Net, Beanshell, Spring, SQL, API REST, Git, SOAP UI, Apache Maven, Méthodologie agile, Eclipse, GitLab CI/CD, LDAP, Active Directory

Key Contributions:

• Developed backend modules for IPv6 integration in 5G router configuration.
• Enhanced Angular components for IPv6 integration.

Environment & Tools: Java17, Spring Boot, Hibernate, SQL, API REST, Git, Angular14, HTML, CSS, MapStruct, Apache Maven, Méthodologie agile, IntelliJ, JUnit, Mockito, GitLab CI/CD

Key Contributions:

• Creation of custom content models
• Creation of different Alfresco sites for different directions of INSERM
• Development of services for documents classification automation

Environment & Tools: Java11/ Spring/ Web scripts /Alfresco Content Service (acs) / Alfresco Search Service (ass) / SGBD PostgreSQL /Docker /Maven / Git / Jenkins/Keycloak

Key Contributions:

• Development of REST APIs using Springboot and user interface (in Angular) for the portal
• Relational database design
• Unit testing and technical documentation

Environment & Tools: Java8, Eclipse, Maven, GitHUb, TypeScript, Angular, Rest Api, Spring boot, Méthodes Agile, JUnit

Key Contributions:

• Development of Deep Learning Pipeline: Design and implementation of a deep learning pipeline to predict the remaining lifespan of vacuum pumps.
• Data Preparation and Processing: Preparation of necessary data for training machine learning models.
• Modeling and Prediction: Application of linear regression, classification, and random forest models for equipment lifespan prediction.
• Analysis and Documentation: Presentation of results with confusion matrices and diagrams, and writing of technical documentation.

Environment & Tools: Python, conda, Jupyter, ST Micro-electronics Cube design, MatplotLib, NumPy, Pandas, Scikit-learn, Seabon, Tensorflow, STEVAL-STWINKT1