Ghazi Ben Henia

• Technologies: Python, SHAP, Autoencoders, TensorFlow, Google Colab • Model Development for Simulation Enhancement: Developed MLP and CNN models with an R² score of 0.98, using benchmark results as data to predict performance under "load" and "no-load" conditions. • Optimization: Created models that enhance simulation results, optimizing for low latency and compact size to support efficient simulations. • Research and Experimentation: Explored ML algorithms for regression tasks to improve accuracy, focusing on refining simulations based on predicted outcomes.

• Technologies: Python, NLP, Google Colab, TensorFlow • Researched healthcare product classification standards and conducted presentations to aid data-driven decisions. • Enhanced data management and retrieval through the use of NLP and CNN models for accurate product categorization based on textual descriptions

• Technologies: C++, Python • Automation of Data Processing: Developed C++ scripts to automate complex data calculations from multiple inputs: - Structural stress analysis for poles to ensure stability and durability. - Thermal analysis for conductors, transformers, and other electrical components to maintain operational safety. • Enhanced computational efficiency and reduced manual intervention. • Technical Reporting: Documented analysis results and presented key insights to technical teams, supporting informed decision-making across projects.

• Technologies: Python, Java, Android Studio, Scikit-learn, PyTorch, Firebase Designed and built mobile applications that let users view and keep track and manage all of the items in their inventories using JAVA and Android Studio. • Achieved a 60% reduction in operational management time by automating the categorization of various products using AI and implementing real- time updates to the database.